Wiser Healthcare, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.
2Sydney Health Literacy Lab, Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.
Objective of the study:
To summarize the patient-reported factors associated with older adults' decisions regarding screening for breast, prostate, colorectal, and cervical cancer.
Method:
21 studies were included.
Factors associated with decision-making were synthesized into 5 categories: demographic, health and clinical, psychological, physician, and social system.
The most commonly identified factors included personal or family history of cancer, positive screening attitudes, routine or habit, gaining knowledge, friends, and a physician’s recommendation.
Results:
Although guidelines suggest incorporating life expectancy and health status to inform older adults’ cancer screening decisions, older adults’ ingrained beliefs about screening may run counter to these concepts.
Consequently, communication strategies are needed that support older adults to make informed cancer screening decisions by addressing underlying screening beliefs in context with their perceived and actual risk of developing cancer.
Cancer Rose commentary
We analyzed the CNGOF (CNGOF-French national college of obstetricians and gynecologists) campaign of 2019, a stunning "cry of alarm" for breast cancer screening in older women, with spectacular media coverage in a clear sky, while no country practicing screening recommends screening beyond the age of 74, nor even the WHO...
Why is this campaign, still relayed on this learned society's homepage, a danger to the elderly?
A study from the University of Leyden provides an answer.
Few trials have focused on screening women in old age. The study by researchers from the University of Leyden on data from the Netherlands, published in 2014 in the BMJ, makes up for this lack.
According to the authors, after the age of 70, organized breast cancer screening would be useless. Indeed, at this age, screening does not significantly improve the detection of advanced cancers but instead increases the number of overdiagnosis and, therefore, overtreatment.
In the Netherlands, breast cancer screening has been offered to women up to 75 since the late 1990s. "Yet there is no evidence that screening older women is effective," the study authors explain, citing that few trials have been conducted specifically on these age groups.
For the Dutch researchers, systematic screening after 70 years of age would mainly lead to the detection and treatment of lesions that would not have developed into disease during the life of the patients.
These unnecessary treatments have a considerable impact on health, and the co-morbidity of these older adults is too high, as they are less able to tolerate the side effects of treatments, such as surgery, radiotherapy, and chemotherapy.
For this reason, they recommend that generalized screening not be extended to those over 70 years of age and recommend an individualized decision based on life expectancy, breast cancer risk, general condition, and preference of the women concerned.
It should also be remembered that the immune system weakens with age. This means that we contract more cancers and infectious diseases. All the organs become exhausted and function less well, and the healing and tissue regeneration faculties are lessened, all of which must be considered when administering heavy treatments.
Conclusion
A point of view published in the JAMA in 2019 raised the question of the relevance of screening for older adults. While all recommendations stop this screening at 74 years of age, it is unfortunately not uncommon to see people beyond that age being sent for screening and "check-ups."
The authors argue that the evidence of benefits for older adults is unclear, and the chance of harm becomes greater (e.g., overdiagnosis, burdens of additional testing, false-positive results, and psychological impacts).
Although aging-related concepts are challenging to communicate, older people must be counseled about the reduced benefit and increased chance of harm from screening associated with limited life expectancy and worsening health to make better quality screening decisions. Communication strategies are needed that support older adults in making informed cancer screening decisions.
The principle of non-maleficence implies not harming people, a principle that even a learned society like the CNGOF must adopt.
Glasgow-communication
The Australian author reported at this week's ICCH2022 INTERNATIONAL CONFERENCE ON
COMMUNICATION IN HEALTHCARE (September 5-9, 2022, Glasgow), the results of an interview-based study involving general practitioners regarding cancer screening in older adults.
Background: Older adults continue to be screened for cancer with limited knowledge of the potential hams. In Australia, general practitioners (GPs) may play an important role in communication and decision-making around cancer screening for older people. This study aimed to investigate GP’s attitudes and behaviours regarding cancer screening (breast, cervical, prostate and bowel) in patients aged ≥70 years (as screening programs recently began targeting ages 70-74). Methods: Semi-structured interviews were conducted with GPs practising in Australia (n=28), recruited through multiple avenues to ensure diverse perspectives (e.g., practice-based research networks, primary health networks, social media, cold emailing). Transcribed audio-recordings were analysed thematically. Findings: Some GPs initiated screening discussions only with patients younger than the upper targeted age of screening programs (i.e., some thought 69 or 74 years). Others initiated discussions beyond recommended ages. When providing information, some GPs were uncomfortable discussing why screening reminders stop, some believed patients would need to pay to access breast screening, and detailed benefit and harms discussions were more likely for prostate screening. When navigating patient preferences, GPs described patients who were open to recommendation, insistent on continuing/stopping, or offended they were not invited anymore, and tailored their responses accordingly. Ultimately the patient had the final say. Finally, GPs considered the patient’s overall health/function, risk, and previous screening experience as factors in whether screening was worthwhile in older age.
Discussion: There is no uniform approach to cancer screening communication and decision-making for older adults in general practice and limited understanding among both older people and GPs around why screening has an upper targeted age. Tools to support effective communication of the reduced benefit and increased chance of harm from cancer screening in older age are needed to support both older people and GPs to make more informed cancer screening choices.
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By Søren R Christiansen, Philippe Autier, Henrik Støvring
The effect of breast cancer screening is declining
A new study raises the debate about the progressive decrease in the benefits of breast cancer screening which would be at a too low level compared to their consequences in terms of overdiagnosis and overtreatment. Researchers from the University of Aarhus, Department of Public Health, Denmark, and the International Prevention Research Institute (IPRI), Lyon, France, are the authors of the study. They state that breast cancer mortality has decreased over the past three decades due to improvements in patient management and better therapies, while the number of women needed to be invited to mammography screening in Denmark to prevent one cancer death in 10 years has doubled.
"As the beneficial effects of mammography screening declines ever more, we should consider abandoning the current mammography screening program with biennial mammograms for everyone aged 50-70. Perhaps a more targeted, high-risk screening strategy could be an alternative, if studies showed the strategy's beneficial effects," Støvring, associate professor in the department of public health at Aarhus University declared in an interview.
"I think we are approaching a point where just continuing might become untenable from an ethical point of view, as fewer and fewer women will experience gains due to screening (they would not die from breast cancer anyway due to improved treatment), but the number of women harmed due to overdiagnosis and overtreatment remains constant," he noted.
H.Støvring believes that for breast cancer the evidence for mammography screening is not convincing. He declared: "I think it is critical that we reassess screening programs as new evidence becomes available”.
In conclusion, improvements in cancer therapy over the past 30 years have reduced mortality, which may erode the benefit-harm balance of mammography screening.
In addition, future improvements in the management of patients with breast cancer will increasingly reduce the benefit-risk ratio of screening.
The benefit of mammography in terms of reduced mortality declines while the harms such as overdiagnosis are unaffected. Screening leads to both overdiagnosis and overtreatment, which has a cost both on a human level and in terms of the economy.
Interview with the main author, June 24, 2022 by Helle Horskjær Hansen
Screening for breast cancer has a cost. This is shown by a Danish/Norwegian study that analysed 10,580 breast cancer deaths among Norwegian women aged 50 to 75 years. "The beneficial effect of screening is currently declining because the treatment of cancer is improving. Over the last 25 years, the mortality rate for breast cancer has been virtually halved," says Henrik Støvring, who is behind the study. According to the researcher, the problem is that screenings lead to both overdiagnosis and overtreatment, which has a cost both on a human level and in terms of the economy.
Overdiagnosis and overtreatment
When the screening was introduced, the assessment was that around twenty per cent of the deaths from breast cancer among those screened could be averted. While this corresponded to approximately 220 deaths a year in Denmark 25 years ago, today the number has been halved.
The study shows that in 1996 it was necessary to invite 731 women to avoid a single breast cancer death in Norway, you would have to invite at least 1364 and probably closer to 3500 to achieve the same result in 2016. On the other hand, the adverse effects of screening are unchanged.
"One in five women aged 50-70, who is told they have breast cancer, has received a 'superfluous' diagnosis because of screening – without screening, they would never have noticed or felt that they had breast cancer during their lifetime," says the researcher.
One in five corresponds to 900 women annually in Denmark. In addition, every year more than 5000 women are told that the screening has given rise to suspicion of breast cancer – a suspicion that later turns out to be incorrect.
Peaceful, small nodes – but in who?
Henrik Støvring notes that the result is not beneficial for the screening programmes.
According to the researcher, the challenge is that we are not currently able to tell the difference between the small cancer tumours that will kill you and those that will not.
Some of these small nodes are so peaceful or slow-growing that the woman would die a natural death with undetected breast cancer, if she had not been screened. But once a cancer node has been discovered, it must of course be treated, even though this was not necessary for some of the women – we just do not know who.
"The women who are invited to screening live longer because all breast cancer patients live longer, and because we have got better drugs, more effective chemotherapy, and because we now have cancer care pathways, which mean the healthcare system reacts faster than it did a decade ago,” says Henrik Støvring.
Abstract of the study
Source:
Søren R Christiansen, Philippe Autier, Henrik Støvring, Change in effectiveness of mammography screening with decreasing breast cancer mortality: a population-based study, European Journal of Public Health, 2022;, ckac047, https://doi.org/10.1093/eurpub/ckac047
Background
Reductions in breast cancer mortality observed over the last three decades are partly due to improved patient management, which may erode the benefit-harm balance of mammography screening.
Methods
We estimated the numbers of women needed to invite (NNI) to prevent one breast cancer death within 10 years. Four scenarios of screening effectiveness (5–20% mortality reduction) were applied on 10,580 breast cancer deaths among Norwegian women aged 50–75 years from 1986 to 2016. We used three scenarios of overdiagnosis (10–40% excess breast cancers during screening period) for estimating ratios of numbers of overdiagnosed breast cancers for each breast cancer death prevented.
Results
Under the base case scenario of 20% breast cancer mortality reduction and 20% overdiagnosis, the NNI rose from 731 (95% CI: 644–830) women in 1996 to 1364 (95% CI: 1181–1577) women in 2016, while the number of women with overdiagnosed cancer for each breast cancer death prevented rose from 3.2 in 1996 to 5.4 in 2016. For a mortality reduction of 8.7%, the ratio of overdiagnosed breast cancers per breast cancer death prevented rose from 7.4 in 1996 to 14.0 in 2016. For a mortality reduction of 5%, the ratio rose from 12.8 in 1996 to 25.2 in 2016.
Conclusions
Due to increasingly potent therapeutic modalities, the benefit in terms of reduced breast cancer mortality declines while the harms, including overdiagnosis, are unaffected. Future improvements in breast cancer patient management will further deteriorate the benefit–harm ratio of screening.
Key points
Assuming a relative effect of mammography screening at 20% on breast cancer mortality, the number of women who needs to be invited to save one life has increased by 87% from 1996 to 2016. (Editor's note: this means that it is currently necessary to screen an ever increasing number of women in order to have a breast cancer death that would be prevented by screening, so it is more difficult to find a woman who has benefited from screening, while the adverse effects do not decrease (overdiagnosis)).
The number of women overdiagnosed with breast cancer per woman saved from dying of breast cancer has increased substantially from 1996 to 2016.
The deterioration in benefit-to-harm ratio of breast screening will continue due to steady improvement in therapies.
This study supports the need for re-evaluation of national screening programmes in high-income countries.
In this paper, the authors exploit a natural experiment resulting from the phased geographic rollout of a national mammography screening programme in Ireland to examine the impact of screening on breast cancer outcomes from both a patient cohort and a population perspective.
Ireland is one of the few countries where, for operational reasons, the rollout of screening has resulted in a cohort of unscreened women that has existed long enough to serve as an appropriate comparison group.
Using data from 33,722 breast cancer cases diagnosed between 1994 and 2011, the authors employ a difference-in-differences research design using ten-year follow-up data for cases diagnosed before and after the introduction of the programme in screened and unscreened regions.
They conclude that, although the programme produced the intended intermediate effects on breast cancer presentation and incidence, these failed to translate into significant decreases in overall population-level mortality, though screening may have helped to reduce socioeconomic disparities in late stage breast cancer incidence.
Highlights of the study
Screening increased detection of asymptomatic and early stage cancers.
There was no significant effect on population breast cancer or all-cause mortality.
Screening may have reduced socioeconomic disparities in late stage incidence.
Results call in to question the overall effectiveness of this common intervention.
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A study conducted by UC Davis Health* found that half of all women screened annually with tomosynthesis** experience at least one false-positive mammogram over a decade of screening.
Reminder: A false positive occurs when a mammogram is indicated as abnormal, but there is no cancer in the breast; this is after verification by other examinations (ultrasound, MRI, sometimes breast biopsy) and after a waiting period for the results between a few days and a few weeks.
Also, to be reminded, false positives in this screening are common. While approximately 12% of 2D screening mammograms are recalled for further investigation because of a false alarm, only 4.4% of these recalls, or 0.5% overall, result in a cancer diagnosis. Thus, women are most commonly alerted and recalled for nothing, resulting in significant moral harm.
* UC Davis Medical Center is part of a major academic health center located in Sacramento, California.
** Tomosynthesis (TDS): Tomosynthesis (or 3-D mammography) is an X-ray imaging technique that decreases the effect of breast tissue overlay by reconstructing a three-dimensional image of the breast from multiple low-dose X-rays acquired at different projection angles.
The objective of the study
This study aims to answer the following question: Is there a difference between screening with digital breast tomosynthesis (3D) vs. digital mammography (2D) in the probability of false-positive results after 10 years of screening?
Method
This is a comparative effectiveness study of 903 495 individuals undergoing 2 969 055 screening examinations.
Results:
The study found that repeated breast cancer screening with 3D mammography only modestly decreased the risk of having a false-positive result compared with standard 2D digital mammography.
The 10-year cumulative probability of at least 1 false-positive result was 6.7% lower for tomosynthesis vs. digital mammography with annual screening and 2.4% lower for tomosynthesis vs. digital mammography with biennial screening. Therefore, the risk of false positives is lower when screening is performed every two years instead of every year, but also in the case of non-dense breasts and for older women. However, as can be seen, the difference is modest, and the reduction in false positives with 3D mammography is only 2.4% compared to standard mammography.
The first author notes, "We were surprised that the new 3D technology in breast cancer screening did not significantly reduce the risk of having a false-positive result after 10 years of screening; however, the risks of false-positive results are much lower with biennial screening compared with annual screening."
Contribution of this study
An earlier study was published in JAMA Oncol in 2018 and suggested that screening with the 3D technique was associated with better specificity (i.e., fewer false positives) and an increased proportion of breast cancers with a better prognosis (smaller and node-free) across all age and breast density groups. As the false positive rate was lowered, this resulted in a decrease in the number of repeat examinations.
We had analyzed this study here (only in French) and highlighted several limitations of this study, starting with the too-small size of the sample. The over-detection problem remained unresolved since the claimed improvement in recalling rates was made at the cost of a significant over-diagnosis.
An article in the BMJ in July 2019 by Jeanne Lenzer, a science journalist, questioned the value of adding tomosynthesis to digital mammography, which she said was unproven. According to this author, the information given to women undergoing this technique, which is on the rise in the United States, is more of a marketing argument than neutral and scientific information.
3D technology has not been integrated into the French screening program due to the uncertainties highlighted by the French High Authority for Health.
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*The Discrete Choice Method (DCM) analyzes consumer choices. Under specific behavioral hypotheses, it makes it possible to explain the trade-offs individuals make between the various attributes of a good or service.
Summary:
Ductal carcinoma in situ (DCIS) is more frequent as it is routinely screened; estimates indicate that 80% of DCIS are of good prognosis and do not threaten women's health. They thus contribute significantly to the overdiagnosis of breast cancer, i.e., needless diagnoses of lesions that, if they had not been found, would not have impacted either the health or the life of women. But almost all DCIS are treated aggressively by surgery, often combined with radiotherapy and/or hormonal therapy, depending on the management guidelines in each country. In some countries, active surveillance is proposed; in others, like France, DCIS are treated with the same aggressiveness as "true" invasive cancers.
However, there are few studies on patients' preferences for treatment options.
Here the question asked is: What trade-offs are women willing to make between side effects of treatment for ductal carcinoma in situ (DCIS) and future risk of invasive cancer?
Main result: A majority of women (71%) were willing to accept a small increase in future risk of invasive cancer for treatment scenarios that offered a reduction in treatment-related side effects.
The results of this study underscore the importance of shared decision making, weighing risks and benefits, between the patient and the caregiver managing a low-risk condition.
Background
The term "overtreatment" has been used to characterize treatment for conditions that look like early cancer but are not destined to cause symptoms during a patient's lifetime or to be a cause of death. It has been estimated that as many as one in four patients with breast cancer detected by screening may be subject to overdiagnosis and overtreatment. Much of this burden relates to treating ductal carcinoma in situ (DCIS or preinvasive breast cancer). In fact, almost all CCIS are treated aggressively with surgery, radiotherapy, and/or endocrine therapy, especially in France.
The 10-year breast cancer–specific survival among women treated for DCIS is 98%-99%, implying that either current therapy is almost completely effective in eradicating breast cancer mortality or many women with DCIS would not have progressed to invasive breast cancer and thus were overtreated.
The exceptionally high breast cancer–specific survival across alternative treatment options has raised concern that in patients who have an indolent form of DCIS, treatment imposes harm without offering significant benefit.
An alternative to standard guidelines that has been proposed is the active surveillance (AS) approach, as is currently offered for many men with early prostate cancer and for women with other conditions considered high risk for breast cancer, such as atypical ductal hyperplasia, lobular carcinoma in situ, or a hereditary deleterious mutation. An AS strategy would entail close monitoring, with the aim of intervening only upon evidence of disease progression.
At the international level, four active prospective clinical trials are testing the safety and benefits of this approach: the LORD trial, which still includes patients.
(Read here: https://clinicaltrials.gov/ct2/show/NCT02492607 -Since February 2019, are also accepted CIS grade II, in addition to grade I -Since July 2020, the randomized trial has been transformed into a patient preference trial: women have the choice of the trial arm (either surveillance or conventional treatment) -Estrogen receptor and HER2 testing has been added before patients are enrolled in the trial to rule out high-grade lesions, to make the trials even safer -There are now 28 sites open in the Netherlands, 6 in Belgium, including a francophone site opened in Brussels : https://www.chu-brugmann.be/fr/research/trials/trial.asp?num=82 15 sites will open in other countries, including France, to come!)
As awaiting the results of these trials, it is important to discern whether AS might be an acceptable option to some women if they were offered the opportunity to evaluate the benefits and harms of alternative management options.
In other words, would women accept other options such as AS instead of standard treatments if the benefit/risk balance was well explained to them? To test this hypothesis, this study elicited patient preferences to quantify how women are willing to accept trade-offs among the possible management options for CCIS, including AS.
Discrete choice experiments, as in this case, are survey-based instruments used to obtain information about preferences for different aspects of goods and services of interest. In a discrete choice experiment, participants are asked to choose between two or more experimentally designed scenarios that require trade-offs across the features (termed "attributes") of a good or a service; here, the management of DCIS; by analyzing participants' choices across questions, it is possible to estimate the relative importance of features on choices and how this orients the choices that persons then make. In oncology scenarios, this may include trade-offs among the additional survival afforded by a proposed cancer treatment and the side effects, inconveniences, or costs associated with that treatment.
Methods
To better understand patient preferences, using a "discrete choice experiment," Hwang and coauthors recruited 194 healthy women in a screening mammography clinic.
Participants were provided with informational videos about the diagnosis and clinical significance of CCIS. Then the women were asked to imagine that they had been diagnosed with CCIS and then choose between several management scenarios that included the option of aggressive treatments, less aggressive treatments, which also included the estimated risk of cancer and the side effects of treatments. Different criteria were defined, such as breast appearance, severity of infection in the first year, chronic pain, hot flashes, and risk of developing or dying from breast cancer within 10 years, to create clinical pictures or "health profiles" for the different scenarios, for a more concrete representation for women depending on the choice they would make.
Results:
Not surprisingly, future risk of breast cancer and its attendant risk of mortality were the most important factors when women evaluated hypothetical management options. However, the study found that over two-thirds of participants were willing to accept some increase in future breast cancer risk to reduce the extent of surgery or the severity and/or duration of treatment-related side effects.
In other words, a majority of women were willing to accept a small increase in a possible future risk of invasive cancer for treatment scenarios that offered reduced treatment side effects.
Conclusion and implication in real life :
This indicates that there is likely a subset of women who, when diagnosed with DCIS, would prioritize a reduction in side effect burden or extent of surgery over future breast cancer risk in certain contexts, researchers concluded.
Most women were willing to make trade-offs between treatment-related effects and risk of invasive cancer, underscoring the need for shared decision making between patients and providers regarding treatment strategies for carcinoma in situ.
Although many discussions of management options for CCIS focus almost exclusively on future breast cancer risk and risk reduction, the results of this study confirm that women benefit if they are presented with detailed information about risks and treatment outcomes, allowing them to make a fully informed, personalized health decision.
The study confirms that treatment choice decisions for CCIS are highly sensitive to personal preferences, and that no a priori assumptions can be made about the trade-offs patients would be willing to consider when weighing the risks and side effects of treatment.
These complex considerations are fundamental to efforts to de-escalate treatments for low-risk conditions such as CCIS.
Advice for Oncologists, interview with principal author:
In an interview, the principal author provides advice to oncologists on how to discuss CCIS treatment options with patients in a thorough and balanced manner. Shelley Hwang, MD, on Helping Patients Make DCIS Management Decisions/Excerpts
Ductal carcinoma in situ (DCIS) is common in the United States, but there are few studies of patient preferences for treatment options. Authors : "Estimates indicate that only 30% of DCIS may progress to invasive cancer. Nevertheless, almost all DCIS is aggressively treated with surgery, often combined with radiation and/or endocrine therapy, according to guideline-concordant care."
To better understand patient preferences, using a "discrete choice experiment, "Hwang and co-authors recruited 194 women without breast cancer from a screening mammography clinic. The women were asked to imagine they had been diagnosed with DCIS and then asked to choose among several scenarios that included aggressive and less-aggressive forms of treatment, estimation of cancer risk, and side effects. Not surprisingly, future risk of breast cancer and mortality were the most important factors when the women evaluated hypothetical management options. However, the study found that more than two-thirds of the participants were willing to accept some increase in future breast cancer risk to reduce the extent of surgery or the severity and/or duration of treatment-related side effects.
This indicates that there is likely a subset of women who, when diagnosed with DCIS, would prioritize a reduction in side effect burden or extent of surgery over future breast cancer risk in certain contexts," the researchers concluded.
In the following interview, Hwang elaborates on the details of the study and how to discuss treatment options with patients.
Do you have any advice for how oncologists can discuss treatment options for DCIS with patients in a thorough and balanced way?
Hwang: One key step is eliciting how much knowledge a patient has about her diagnosis and its implications. I think a surgical oncologist would tend to jump right in and say, it's a cancer, we need to remove it, these are the surgical options. That's always the easiest thing for us to do, but we sometimes neglect to spend time with the patient upfront talking about the diagnosis itself and what the clinical implications are. And when you're dealing with a disease that has no immediate clinical or life-threatening implications, and specifically for DCIS when we don't even know if it will turn into cancer even if we don't intervene surgically, I think framing the diagnosis first and making sure the patient understands the implications of the diagnosis is important.
Your study used discrete choice experiments, which were first developed for market research. Can you briefly describe how these work?
Hwang: Discrete choice experiments have been used a lot in areas such as health economics to see how people make decisions and weigh pros and cons of all the different aspects of making that decision. So say you're about to buy a house, not only do you have to consider cost but also location, how many bedrooms it has --there are many different components that go into that decision. It's never just one driver that makes an individual decide which house to buy. There are some very emotional aspects to that too. So a discrete choice experiment tries to come up with a set of attributes that are important for making a certain kind of decision.
In this case it was a diagnosis of DCIS and the decision about how to manage it. We tried to include attributes we thought would be meaningful for patients. So postoperative pain, for instance -- that's something people wonder about and are concerned about. We included different levels of pain in the experiment. Cosmesis and side effects of treatment are also important considerations. We created different scenarios where we mixed and matched these different attributes. We presented them to patients and asked them to choose which scenario most matched their preferences. That gave us an idea of what values patients considered most important when trying to make a decision about DCIS.
I think this is something that's becoming more and more relevant. Cancer screening detects precancers such as DCIS that have no immediate clinical implications. There are no symptoms, there are no mortality implications, there's just this concern, that we're trying to prevent cancers from occurring. And I think the better we are at screening, the more we're going to find ourselves in this position, not only with cancer but also with cardiac disease and metabolic diseases, where we diagnose a condition before the patient has any symptoms.
So I think balancing the pros and cons is a lot more relevant when you're not dealing with immediate life-threatening illnesses, and learning how to talk to patients about these scenarios will be an increasingly important skill.
Your study included women without an actual diagnosis of DCIS. Do you think this limits the generalizability of your results to the general DCIS population?
Hwang:That's a really good point. We didn't feel we could do this study with women who were diagnosed with DCIS, because we didn't know what information they would come in with already. If someone somewhere along the way said to them you have cancer and it needs to come out, that could certainly affect how they viewed their choices. To do this discrete choice experiment, we needed a group of patients that didn't have a lot of other sources of information about the disease already. ...........
On the other hand, women in the study were coming in and presenting with an abnormality, or they were coming for a breast cancer screening, so they were already thinking about what would happen if they did have a diagnosis. So we felt like it wasn't a stretch to use this population.
We as surgeons are taught to focus on cancer outcomes and mortality, and we should focus on those things. However, sometimes our training hasn't incorporated how to balance other things that patients care about and helping them apply these values to a treatment decision that's comfortable or preferable to them.
I've found that sometimes surgical oncologists, and oncologists in general, treat the cancer, but what we really need to do is holistically treat the patient along with the cancer. That's the take-home message of this study, underscoring how important it is to treat each person as a unique individual and someone who may not necessarily share the treating provider's belief system.
There is room in medicine to accommodate many differing views of risk and health.
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According to a modeling study based on data from Breast Cancer Surveillance Consortium (BCSC), about one in six to seven screened breast cancer cases is overdiagnosed.
This study first highlights that overdiagnosis in breast cancer screening is real.
Results of study
An average of 15.4% (95% CI: 9.4%-26.5%) of screened cancer cases were estimated to be overdiagnosed, reports lead author Marc D. Ryser* of Duke University in Durham, North Carolina, and colleagues.
* Ryser: Marc Daniel Ryser, Assistant Professor of Population Health Sciences. Dr. Marc Ryser is an expert in mathematical and statistical modeling. His research uses biological, clinical, and population-level data to inform and guide the early detection and prevention of cancer.
Below are the results by age group and type of cancer detected (Figure 3 and Table 3).
Beyond the average values, we can observe (Fig 3) that for all age groups, the rate of overdiagnosis can reach maximum values higher than 20%, and according to Table 3, the rate of overdiagnosis at the first screening reaches a maximum value of 28%, at 58 years 21.1%, at 66 years 25.4% and at 74 years 31.9%
In this model study, an interesting finding is that the rate of overdiagnosis increased with age and almost doubled depending on the age range analyzed: 11.5% (95% CI, 3.8%-28.3%) at the first screening at age 50 to 23.6% (95% CI, 17.7%-31.9%) at the last test at age 74.
Comparison with previous data
The authors note, "comparison of our estimates against those from other studies is not straightforward because of differences in overdiagnosis definitions and screening practices."
They conclude that their results regarding overdiagnosis are both higher than previous modeling studies (ranging from 1% to 12%, depending on the studies cited in the article) because of differences in screening practices, diagnostic practices, and modeling assumptions, but lower than other studies that have shown rates much higher than the average in this study. For example, the Canadian screening trial estimated an overdiagnosis rate of 30% (Baines CJ, To T, Miller AB. Revised estimates of overdiagnosis from the Canadian National Breast Screening Study. Prev Med. 2016;90:66-71. [PMID: 27374944] doi:10.1016/j.ypmed.2016.06.033 ) for cancers detected by screening. In a population-based study, Bleyer and Welch (Bleyer A, Welch HG. Effect of three decades of screening mammography on breast-cancer incidence. N Engl J Med. 2012;367:1998- 2005. [PMID: 23171096] doi:10.1056/NEJMoa1206809 ) estimated that 31% of all diagnosed breast cancer cases were overdiagnosed.
The authors conclude with the hope that their findings will join a consensus and facilitate decision-making regarding mammography screening.
Conclusions of the Editorial "Reducing the Burden of Overdiagnosis in Breast Cancer Screening and Beyond
The editorial published in conjunction with the study emphasizes the importance of informing women about what this overdiagnosis represents. (Marcondes FO, Armstrong K. Reducing the Burden of Overdiagnosis in Breast Cancer Screening and Beyond. Ann Intern Med. 2022 March 1. doi: 10.7326/M22-0483. Epub ahead of print. PMID: 35226534.)
Authors underline: « Women who are considering having mammography screening should be counseled about the risk for unnecessary cancer treatment using this information." Estimating that about 60% of the 280,000 cases of breast cancer diagnosed each year in the United States are discovered through mammography screening, eliminating overdiagnosis could save 25,000 women the cost and complications of unnecessary treatment.
"Substantial advances" in critical areas need to be made, according to the authors, including: - Develop a better predictive capability to accurately identify tumors that will not progress - Improve the accuracy of screening technologies to reduce the risk of overdiagnosis and improve the ability to detect breast cancer that has not been detected by mammography -Implement prevention strategies to reduce the overall rate of breast cancer diagnosis, such as providing counseling on lifestyle changes and screening for genetic risk.
The authors of the editorial conclude: « Screening tests, whether for cancer or other conditions, can provide great benefit by detecting disease when it is more easily treatable. However, the risk of labeling millions of persons as having a disease without improving their outcomes is very real. For now, the key to navigating these tradeoffs remains open and effective physician–patient communication, rigorous evaluation of all proposed screening strategies, and continued investment in early detection research. We look forward to the day when making an early diagnosis always helps our patients achieve better outcomes. »
And the findings go beyond breast cancer screening. "As screening and diagnostic testing continues to grow in clinical practice, the issue of overdiagnosis is being felt far beyond cancer screening. For some conditions, changing definitions have led patients to be labeled with a predisease state on the basis of a test result that was previously considered in the normal range. Although there are strong arguments in favor of early treatment to prevent long-term complications in many conditions, the reality is that, just as with cancer screening, there is little doubt that some patients diagnosed through a screening test would never have progressed and are likely to be receiving unnecessary treatment."
Comments and criticisms, opinion of Dr. V.Robert, statistician
1-A modeling study
The study remains a modeling study, which means that the results of a model depend on a chosen model and conditions of validity, at best unverifiable and at worst questionable. For example, the authors are obliged to consider that a breast cancer is either definitively non-evolving or inexorably evolving, with no possibility that the evolutionary status of cancer changes over time. It is not clear that things are that simple.
Another example is that the authors are obliged to build their model by considering that all progressive breast cancers evolve at the same rate and that this rate remains constant throughout the evolutionary period. In practice, there are most likely different distributions of progression rates for each type of breast cancer, and it is not clear that progression rates cannot vary over time.
2- The data on mortality from causes other than breast cancer used by the study do not seem well adapted.
On the one hand, after checking reference 25 of the study, which corresponds to the source of these data (Contribution of Breast Cancer to Overall Mortality for US Women): for a population of women aged 50 to 80 years, these data are not derived from direct measurements of mortality but from data estimated from projections (in other words, from models).
On the other hand, the data correspond to a cohort of women born in 1971. Since the median age of the women included in the study is 56 years, the cohort born in 1971 is adapted for the mortality of women included in 1971 + 56 = 2027. Or, if you prefer, the cohort adapted to have the mortality of women aged 56 in 2000-2018 should be born between 1944 and 1962. Whatever the reasoning, it is clear that the cohort considered to obtain the mortality data is too recent by at least a decade. This is not neutral since the tables in Reference 25 show a non-negligible decline in mortality over time.
3-The definition of screen-detected cancers is questionable.
Screen-detected cancers are considered to be those that meet the following two conditions: screening mammograms BI-RADS 3 to 5 + diagnosis of cancer within the next 12 months. With criteria such as these, interval cancers are likely to be classified as screen-detected cancers (BI-RADS 3 + negative complementary examinations = screening showing no cancer; if a cancer occurs 11 months after the screening mammogram, it is an interval cancer, and yet it will be classified as a screened cancer). Even if these cases are not very frequent, they are part of the data used to adjust the parameters, and adjusting on "garbage in, garbage out" data can only give garbage results.
4- It is wrong to pretend that the study found that the overdiagnosis rate is 15%.
The reality is that the study shows that the overdiagnosis rate is somewhere between 9% and 27% (and any value within that range is possible, no more 15% than 9% or 27%).
Figure 3 from the study:
Depending on the age range, the percentage of overdiagnosis can vary up to 25% or even 32%.
Unfortunately, it is a very common mistake to take the result of a study (estimated rate from a sample) for the reality (real and unknown, rate in the population). And it is an even more common mistake to believe that the estimated rate is more likely to be close to the real rate than any other value in the confidence interval.
Conclusion
Based on such a study, we cannot arbitrarily consider that the debate on the frequency of overdiagnosis is closed, with a definitive frequency of 15%, as the study's authors would like.
On the other hand, the model may be interesting for answering questions about the evolution of the frequency of overdiagnosis as a function of the age of the women screened or about the evolution of the frequency of overdiagnosis as a function of the interval between two screening mammograms.
Professor Alexandra Barrat of the University of Sydney, interviewed by Amanda Sheppeard, associate editor and reporter for Oncology Republic and The Medical Republic, said there are different methods for estimating the potential rate of overdiagnosis through breast cancer screening. She said the study demonstrated the inevitability of overdiagnosis in screening for a number of cancers. "I think there is a need in the professional community for greater acceptance of what the evidence shows about breast cancer screening." "We just need to recognize that this is inherent in a cancer screening program."
As a result, and beyond the evidence, according to A.Barrat, the study helped to underscore the importance of informed consent in breast cancer screening.
Seno’s first clinical product targets the diagnosis of breast cancer and will be used in addition to screening mammography, integrating opto-acoustics and ultrasound.
Cancer Rose est un collectif de professionnels de la santé, rassemblés en association. Cancer Rose fonctionne sans publicité, sans conflit d’intérêt, sans subvention. Merci de soutenir notre action sur HelloAsso.
Cancer Rose is a French non-profit organization of health care professionals. Cancer Rose performs its activity without advertising, conflict of interest, subsidies. Thank you to support our activity on HelloAsso.
This case involves a 65-year-old woman who began mammograms at age 40 due to a family history of breast cancer (mother at age 80). She has already had biopsies, which revealed that she had a simple mastosis (benign condition of the breast, characterized by tension and pain in the breasts, as well as a "granular" consistency when palpating the breasts, in areas where the mammary gland is more present and dense).
A mammogram revealed two small foci of microcalcifications in one breast. A preliminary macrobiopsy was carried out, but it was unsuccessful due to difficulties in locating them. A few months later, a second macrobiopsy was performed.
The two biopsied sites revealed a carcinoma in situ (ductal carcinoma) and an "atypical hyperplasia" lesion. Due to the presence of two concomitant lesions, a complete mastectomy (complete removal) of the breast was recommended based on the pathology report.
Anatomopathology is not infallible
Breast biopsy samples can be difficult to analyze.
In a 2016 study published in the BMJ, American researchers assessed the effectiveness of 12 different strategies in reducing interpretation errors (second opinion requested for all samples, second opinion only in the case of atypia, or only in the case of the wish of the first pathologist or for first readers with less experience in breast pathology, etc...).
115 pathologists examined 240 breast biopsy specimens, one slide per case, and compared their observations to an expert consensus diagnosis.
This study revealed that pathologists who took part in the study disagreed with the expert panel's consensus about 25% of the time. Most of the disagreements were with specimens from difficult-to-interpret conditions, such as atypia, which occurs when cells appear abnormal but are not cancerous, and ductal carcinoma in situ (DCIS)
The conclusion of the study:except for invasive cancer cases where the second opinion rarely differs from the initial interpretation, ALL strategies requiring a second opinion improve diagnostic concordance and reduce misclassification rates of breast specimens from 24.7% to 18.1%, showing that variability in diagnosis is still only incompletely eliminated, especially for breast specimens with atypia.
A second opinion is thus recommended because it can mean the difference between a diagnosis of benign hyperplasia or carcinoma in situ, influencing surgical sanctions, the need for re-intervention, radiotherapy, and/or chemotherapy.
As a result, a second opinion can help patients make a therapeutic choice.
Why not propose a more systematic second reading of the biopsy?
In the case of a positive biopsy, the start of the disease is defined by this single examination of the tissue taken under the microscope (i.e., except for invasive cancer, where uncertainty is rarer) (histological diagnosis).
And it is astounding to note how, on the one hand, DCIS is considered a “stage 0” breast cancer with a very good prognosis, and how, on the other hand, the therapeutic sanctions for this DCIS and a fortiori for pre-cancerous lesions can be extremely aggressive, as aggressive as for a "true" invasive cancer.
The patient does not know the name of the person who read her biopsy; worse, she does not have the choice of the reader of her biopsy, the anatomopathologist, contrary to the choice she has for the general practitioner, the gynecologist, and even a surgeon if necessary.
This pathological anatomy report is never communicated to the patient, although it is strictly necessary and mandatory for treatment to begin. It determines the course of treatment and the therapeutic options available.
On the other hand, the pathology report is part of the patient's file and can thus be requested by the patient.
Recommendations for patients if carcinoma in situ or a borderline or atypical lesion is found.
First and foremost, don't panic; take your time. You have the following options:
1- Request that the biopsy results be sent to you physician.
2- In the event of a failure, request a complete copy of the medical file (mandatory within 8 days)
3- If you are unsuccessful, request that the Medical Council intervene to obtain it for you. You are the owner of the medical file.
4- With the result, it is legitimate to ask for a revision of the anatomopathology slides. You can even have the file re-examined by an expert (your general practitioner just has to ask for it).
5-It is also possible to ask for a second opinion from another surgeon, possibly located in another region.
The therapeutic choice can be discussed: a less aggressive intervention or even simply "careful monitoring," knowing that unfortunately in France, for the moment, very few practitioners are adept at this wait-and-see approach which is being studied in several large European trials, including the LORD trial which is still including patients.
(-Since February 2019 are also accepted CIS grade II, in addition to grade I
-Since July 2020, the randomized trial has been transformed into a patient preference trial: women have the choice of the trial arm (either surveillance or conventional treatment)
Estrogen receptor and HER2 testing has been added before patients are enrolled in the trial to rule out high-grade lesions, to provide even greater safety in the trial
-There are now 28 sites open in the Netherlands, 6 in Belgium, and 15 sites will open in other countries (France, to come!)
Conclusion
An anatomopathological diagnosis should be reviewed and discussed by caregivers, rather than being accepted as a "gold standard" because it may trigger a series of aggressive treatments, the usefulness of which should be discussed with the patient.
Cancer Rose est un collectif de professionnels de la santé, rassemblés en association. Cancer Rose fonctionne sans publicité, sans conflit d’intérêt, sans subvention. Merci de soutenir notre action sur HelloAsso.
Cancer Rose is a French non-profit organization of health care professionals. Cancer Rose performs its activity without advertising, conflict of interest, subsidies. Thank you to support our activity on HelloAsso.
This graphic is based on the Cochrane meta-analysis and M. Baum's study on the consequences of screening when treatment effects are considered.
Cochrane Data
The Cochrane Collaboration (currently the Cochrane Organization) is a non-profit organization composed of volunteer researchers from all over the world who are financially independent of the pharmaceutical industry.
This collaboration aims to systematically organize scientific information and medical research data based on properly conducted clinical trials. The scientifically validated data are summarized in an accessible way and published in the Cochrane library.
To assess the screening results and weigh the benefits and risks, researchers gathered data from all previous screening studies, which included 600,000 women – both screened and not screened. They combined the findings of all studies conducted since the 1970s to compare the benefits and harms of each situation. To make their results more concrete, they projected them onto two fictitious populations of 2 000 women in the form of a "dot chart."
Each dot represents a woman. Researchers from the Cochrane Collaboration indicate overdiagnosis (red dots), false alarms (blue dots), avoidable deaths (dark dots), and deaths (black dots) to provide a comparative picture of what happens when you have a screening versus when you don't.
Michael Baum is an Emeritus Professor of Surgery, Division of Surgery and Interventional sciences, University College London, London WC1E 6BT, United Kingdom.
According to this researcher, when treatment-related deaths are included in the mortality count, the harms of breast cancer screening outweigh the benefits.
These deaths must be considered because the expected benefit of screening (the golden dot materializing the 'life saved') is outweighed by the death due to therapeutic complications (the green dot materializing the 'life shortened' by damage caused by surgery, radiotherapy, chemotherapy, and hormone therapy).
Quote from the last paragraph of the study:
"If each of those were translated into total lives saved from all causes then I would remain content but, unfortunately, when 10 000 are screened along the way about 120 to 140 cases will be overdiagnosed with the current age group invited. Four fifths of these women would receive radiotherapy and would be at an increased risk of dying of ischaemic heart disease and lung cancer. Knowing the background risks (box 2) and multiplying these by the factors 1.27 and 1.78 gives us increases of 2% for lung cancer and 1.33% for myocardial infarction. Adding that to all cause mortality rates I crudely estimate that an additional one to three deaths might be expected from other causes for every breast cancer death avoided."
Cancer Rose est un collectif de professionnels de la santé, rassemblés en association. Cancer Rose fonctionne sans publicité, sans conflit d’intérêt, sans subvention. Merci de soutenir notre action sur HelloAsso.
Cancer Rose is a French non-profit organization of health care professionals. Cancer Rose performs its activity without advertising, conflict of interest, subsidies. Thank you to support our activity on HelloAsso.
Duggan C., Trapani D., Ilbawi A., Fidarova E., Laversanne M., Curigliano G. et al. National health system characteristics, breast cancer stage at diagnosis, and breast cancer mortality: a population-based analysis DOI:https://doi.org/10.1016/S1470-2045(21)00462-9
Concept of early clinical diagnosis
The authors make a distinction in their article between screening and early detection of breast cancer symptoms.
We therefore distinguish :
-Anticipated diagnosis = screening, which is based on repeated mammograms, as practiced in many countries.
- Early clinical diagnosis = the earliest possible detection of the first symptoms of breast cancer; this detection relies on the training and information of women and physicians and/or midwives (caregivers in general), on the one hand by raising their awareness (remembering to look for the symptom in the breast), and on the other hand by educating them on 'what' to look for.
- This concept of early clinical diagnosis contrasts with a late diagnosis due to the presence of symptoms of existing cancer that have been neglected for a long period due to a lack of information for women and a lack of training for caregivers.
The authors note that some countries do as well with early symptom detection as countries that use screening.
The Lancet article suggests that early diagnosis may work as well as screening.
Ukraine appears to have chosen this option, which is appropriate for developing countries that cannot afford routine mammography screening.
However, we can draw a pertinent question and a lesson from these findings for our countries where campaigns are in full swing, with mammographic screening, which no longer demonstrates its effectiveness and has drawbacks: What if early detection had a better benefit/risk ratio than routine mammographic screening?
Reducing breast cancer mortality with less overdiagnosis
The findings of the study, published in The Lancet Oncology, support the WHO recommendation, implying that early clinical diagnosis may be as effective as screening in avoiding advanced cancers and lowering mortality from breast cancer.
The benefit-risk balance of early diagnosis may be better than that of mass screening because it eliminates overdiagnosis and overtreatment caused by mammographic screening.
A serious alternative
As explained in detail on the website of Dr. Vincent Robert, statistician, this is an alternative to both screening and "doing nothing."
The idea, promoted by the WHO and confirmed by the Lancet study, is to offer this option to women to broaden their range of options and allow them to choose the path that appears to be most suitable for them, with full knowledge of the facts.
Cancer Rose est un collectif de professionnels de la santé, rassemblés en association. Cancer Rose fonctionne sans publicité, sans conflit d’intérêt, sans subvention. Merci de soutenir notre action sur HelloAsso.
Cancer Rose is a French non-profit organization of health care professionals. Cancer Rose performs its activity without advertising, conflict of interest, subsidies. Thank you to support our activity on HelloAsso.
With the emergence of predictive software [1] the radiological criterion of breast density, i.e., the predominance of fibroglandular tissue over fatty tissue in the female breast, has become, despite the lack of conclusive studies, a risk factor for breast cancer on its own. Breast density is generally high in young, non-menopausal women (but may persist after menopause), in leaner women with low body fat, and in women undergoing hormone replacement therapy during menopause.
As we said, it is a radiological criterion; whether this characteristic is really associated with an increased risk of cancer, opinions diverge and the question is far from being decided in the course of studies, which does not prevent opinion leaders from raising the scarecrow of dense breasts to terrorize women, if need be....[2]
What is established, however, is that with high breast density the discriminating power of mammography and the ability of the radiologist's eye to detect a lesion are greatly diminished, and it is only a short step from there to make a shortcut between breast density and cancer risk.
Available studies
Several studies are available, starting with the Wolfe study [3] on the relationship between breast density and breast cancer risk. This old study was strongly contested at the time, even by the supporters of screening.
Other studies have since been published, studying the relevance of linking this density factor with other risk factors, in order to develop models for calculating the risk of contracting breast cancer within 5 years. [4] [5] [6] [7] [8] [9] [10]
Today, there is no convincing evidence that high breast density is associated with risk of death from breast cancer. Today, no tool for estimating the risk of breast cancer using breast density has yet proven its relevance.
The HAS(Higher Authority for Health in France), in a work on the identification of risk factors, writes:
"High pre-menopausal breast density was not retained as a risk factor at the end of the work of part 1."[11]
The viewpoint published in JAMA on May 9, 2019[12]
The background is the adoption by the US Congress of legislation on breast density.[13]
More precisely this legislation requires the US Food and Drug Administration (FDA)[14] as part of the regulatory process to ensure that all mammography reports and summaries provided to patients include information on women' s breast density. This authority, which oversees the regulation of mammography facilities and quality standards, has previously required the reporting of breast density in radiologists' reports.
Based on published studies (see our bibliography), and according to the authors of this viewpoint published in JAMA, breast density as a risk factor for developing breast cancer draws attention to the fact that the associated increase in cancer risk is modest, and that for women diagnosed with breast cancer, increased breast density was not associated with an increased risk of poor-prognosis cancer or death from breast cancer.
Dense breasts are common (43% of women aged 40 to 74 years) and the majority of women with dense breasts will not develop breast cancer....
According to the editors of this article, notification of breast density may increase confusion and anxiety related to mammography and breast cancer, without providing clear recommendations on what women with dense breasts should do.
The USPSTF [15], in 2016, concluded that there was insufficient evidence to recommend additional breast imaging in women with dense breasts. This group raises several points of concern with this legislation requiring notification of breast density information to women.
Significant variability and limited reproducibility in the determination of dense breasts. This variability exists on an examination whether it is read by one radiologist or by different radiologists. The exam for a given patient may have different classifications and lead to misunderstandings leading to a reduction in a woman's confidence in screening in general, and confusion about her own breast cancer risk.
Uncertainty about initiatives undertaken by women who have been notified of significant breast density to reduce their risk of dying from breast cancer. This refers to the request for additional tests for which there is no evidence to support the indication, as there is no evidence that the addition of imaging other than mammography in women with dense breasts will reduce cancer mortality; instead, these additions increase false positives, unnecessary biopsies, and overdiagnosis. The recall rate is significantly increased by the addition of ultrasound (by 14%), and by the addition of MRI (from 9 to 23%) with low PPVs[16] and an obvious additional cost. The authors remind us that MRI, often considered to be harmless, is likely to have a (small) excess risk of nephrogenic systemic fibrosis, and uncertain risks of gadolinium deposition in the brain when the examinations are repeated. Tomosynthesis (TS) is mentioned as an additional technique used, but the authors point out that longer-term studies are needed to determine whether the routine use of TS in women with dense breasts leads to a real improvement in breast cancer outcomes (mortality, decrease in the rate of serious cancers).
Difficulty in communicating information about breast density to patients. Experts consider this communication difficult and dependent on the literacy level of the population. Study results show poor understanding and confusion and misinformation of patients when information about breast density is given.
Impact Analysis of FDA[17]
In this analysis the FDA claims that mandating breast density reporting would reduce breast cancer mortality in women, as well as costs through early detection of cancers .... But the authors of the viewpoint point to a troubling lack of evidence to support this arbitrary conclusion.
The FDA analysis failed to include in its calculation the costs associated with overdiagnosis, with overtreatment due to additional tests, and the costs of additional visits to primary care physicians.
In conclusion
The authors believe that breast density notification has implications for public health and that physicians, researchers, public health experts, and organizations should take a stand against this imposed rule.
Breast density notification could give clinicians and patients the opportunity to discuss a particular woman's risk of breast cancer, which depends on many factors other than breast density.
Predictive models of breast cancer risk include breast density, but its addition improves predictive estimates little. The addition of complementary imaging should be limited to high-risk women based on other risk factors to be included than breast density alone.
Discussions about the potential benefit of additional imaging for dense breasts should focus on the lack of evidence for a reduction in breast cancer deaths, and the well-known increase in false positives, unnecessary biopsies, and increased health care costs, as well as increased overdiagnosis and overtreatment.
In particular, when deciding on annual surveillance for high-risk women, these elements should be taken into consideration.
Clinicians should also engage patients in discussions about the importance of lifestyle (limiting alcohol, avoiding obesity, regular exercise) to reduce breast cancer risk.
Research will be needed to improve the coherence of reports on breast density and the quality of communication.
Additional research will also be essential to judge the long-term outcomes of complementary imaging to determine whether the benefits outweigh the harms.
But the authors point out that such studies will be increasingly difficult to conduct if the use of complementary imaging is routinely incorporated into screening mammography in women with dense breasts, which is currently the case (Editor's note).
"Mammographic screening should be individualized based on a woman's age, breast density, history of breast biopsy, family history of breast cancer, and knowledge regarding the benefits and harms of screening."
The Contributions of Breast Density and Common Genetic Variation to Breast Cancer Risk Article (PDF Available) in JNCI Journal of the National Cancer Institute 107(5) · May 2015 with 77 Reads DOI: 10.1093/jnci/dju397 · Source: PubMed Celine M Vachon
[6] McCormack VA, dos Santos Silva I. Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. Cancer Epidemiol Biomarkers Prev. 2006;15(6):1159–1169 https://www.ncbi.nlm.nih.gov/pubmed/16775176
[7] KERlikowske K, Cook AJ, Buist DS, et al. Breast cancer risk by breast density, menopause, and postmenopausal hormone therapy use. J Clin Oncol. 2010;28(24):3830–3837. https://www.ncbi.nlm.nih.gov/pubmed/20644098
Breast Cancer Research and Treatment May 2012, Volume 133, Issue 1, pp 1–10| Cite as
Risk prediction models of breast cancer: a systematic review of model performances Thunyarat Anothaisintawee, Yot Teerawattananon, Chollathip Wiratkapun
"Most (risk prediction) models have produced relatively low discrimination in internal and external validations. This low discriminative accuracy of existing models may be due to a lack of knowledge of risk factors, heterogeneous subtypes of breast cancer, and different distributions of risk factors among populations."
[9] McCarthy AM, WE Barlow, Conant EF, et al; Consortium PROSPR. Cancer du sein de mauvais pronostic diagnostiqué après mammographie de dépistage avec résultats négatifs. JAMA Oncol . 2018; 4 (7): 998-1001. doi: 10.1001 / jamaoncol.2018.0352
"Breast density has received much attention as a primary factor identifying the need for additional screening, but it may be more effective to consider both breast density and age to identify women at risk for poor prognosis breast cancer."
[10] Gierach GL, Ichikawa L, Kerlikowske K, et al. Relation entre la densité mammographique et la mortalité par cancer du sein dans le Consortium de surveillance du cancer du sein. J Natl Cancer Inst . 2012; 104 (16): 1218-1227. doi: 10.1093 / jnci / djs327
"High mammographic breast density was not associated with risk of death from breast cancer or any cause after controlling for other patient and tumor characteristics. Thus, risk factors for breast cancer development may not necessarily be the same as factors influencing risk of death after breast cancer development."
[14] The Food and Drug Administration is the U.S. Food and Drug Administration.
[15] Melnikow J, JJ Fenton, Whitlock EP, et al. Supplemental breast cancer screening for women with dense breasts: a systematic review for the US Preventive Services Task Force.
(USPSTF, United States Preventive Services Task Force is an independent U.S. preventive services task force of primary care and prevention experts that systematically reviews evidence of effectiveness and develops recommendations for clinical preventive services).
16] Positive predictive value, which is the likelihood that the subject actually has cancer when he or she has a positive test.
[17] Office of Policy, Planning, Legislation and Analysis, Office of the Commissioner, Food and Drug Administration. Mammography Quality Standards Act; Amendments to Part 900 Regulations: File No. FDA-2013-N-0134.
Mammography Quality Standards Act; Amendments to Part 900 Regulations (Proposed Rule) Regulatory Impact Analysis
Cancer Rose est un collectif de professionnels de la santé, rassemblés en association. Cancer Rose fonctionne sans publicité, sans conflit d’intérêt, sans subvention. Merci de soutenir notre action sur HelloAsso.
Cancer Rose is a French non-profit organization of health care professionals. Cancer Rose performs its activity without advertising, conflict of interest, subsidies. Thank you to support our activity on HelloAsso.
Effect of screening by clinical breast examination on breast cancer incidence and mortality after 20 years: prospective, cluster randomised controlled trial in Mumbai
- Contribution of Dr M.Gourmelon for the decoding the presentation of the risks of mortality. Appendix b
- Contribution of Dr V.Robert for the statistical analysis. Appendix c
27/02/2021
Three randomized controlled trials were conducted in Russia, China and the United Kingdom [appendix a] involving a total of almost 400,000 women, which showed neither a decrease in breast cancer mortality nor a decrease in mastectomies. On the other hand, false positives were increased, leading to additional examinations and biopsies with normal results, and they also caused an increase in women's anxiety.
There was also a question of screening by trained professionals, the problem being the reproducibility from one practitioner to another which is not good. In short, clinical breast examination as a routine screening method has not been retained, as breast self-examination does not ultimately prove to be an effective method for the early detection of breast cancer. And it is still unclear whether screening by clinical breast examination can actually reduce breast cancer mortality
An Indian trial
A new study using the idea of clinical breast examination as mass screening is being conducted by a team of researchers in Mumbai, who are publishing the results of their 20-year randomized controlled trial.
The objective of the study was to test the effectiveness of breast cancer screening by clinical examination in reducing mortality from the disease and also in reducing the stage of cancer at diagnosis, compared with no screening.
151,538 women aged 35 to 64 years with no history of breast cancer participated in the study. Women in the screening group (75,360) received four rounds of clinical breast examination screening (performed by trained primary care professionals) and cancer awareness information every two years. Women in the control group (76,178) received information on cancer awareness and eight rounds of active surveillance every two years.
It is examined whether, in the screening group, the cancer found is of a lower stage at the time of diagnosis compared with unscreened women, and of course whether mortality from the disease has decreased.
The main results of the study are as follows:
-Clinical breast examination performed every two years by primary care professionals significantly reduced the stage of breast cancer at diagnosis. -Clinical breast examination led to a non-significant 15% reduction in overall breast cancer mortality; BUT this is a relative reduction, i.e., for the screened group compared to the unscreened group (control group). See: [appendix b] -The authors conclude that there was a significant reduction of nearly 30% in mortality in women aged ≥ 50 years. BUT This is a subset analysis done post hoc, not provided for in the original study protocol, so after the data were known; again, this is not an absolute reduction but a relative reduction in risk by comparing two groups. See: [appendix b] -No significant reduction in mortality was observed in women under 50.
From the authors' perspective, what the Mumbai trial provides:
-In this 20-year study, clinical breast examination by trained health workers in Mumbai led to a reduction in breast cancer at diagnosis and a reduction in mortality from the disease by nearly 30% in women aged 50 years and older, but with no reduction in mortality observed in the group of women under 50 years. -A 5% reduction in all-cause mortality was observed in the screening arm compared with the control arm, but this was not statistically significant. -Clinical breast examination should be considered for breast cancer screening in low- and middle-income countries.
Review of the Study for Robustness
We present here the analysis of Dr. Robert, statistician of the Cancer Rose group, which you will find more exhaustively in the appendix at the end of the article [Appendix c].
In his opinion, the post-hoc analyses [1], which are included in the abstract and in the conclusion, are problematic.
We summarize his main conclusions about the study:
1-Post-hoc analyses raise suspicions of either a lack of scientific rigor or a lack of objectivity, with a propensity to want to demonstrate a posteriori, by an analysis not previously foreseen in the study protocol and made on the basis of the available data, at any price the effectiveness of screening by clinical breast examination.
2-The study is presented as randomized but in fact it is a cluster randomization (by groups of individuals and not by individuals). The authors do not give any information on the size of the clusters, nor on their characteristics. It is therefore impossible to know whether or not the randomization is sufficient to make the 'screened' and 'control' groups comparable.
3-The manner in which deaths are attributed (cause of death by breast cancer or other cause?) is debatable. When two physicians consulted to determine the cause are unanimous, the cause is retained, but if there is a disagreement a third opinion is required and the majority of opinions prevail; a rigorous process would require eliminating the disputed case.
Other remarks
Of course, there is a certain rate of over-diagnosis which dilutes the number of more advanced cancers in the total number of cancers found. This means that, as the results are expressed as a percentage, one has the impression that there are more cancers of an earlier stage in the screened group. It is surprising that the BMJ accepts this presentation in percentages which biases the results. And indeed, there are overall more women with breast cancer in the screening arm (198) than in the control arm (151).
(It is known that the presentation in percentages embellishes the data and gives a fictitious perception of reality.)
Thus, in Appendix 4 of the report of the citizens' consultation [Appendix d] (page 155) for example, since the citizens had asked for an honest rendering of the data, graphic representations are proposed of what the percentages represent "in real life").
The main point is that the overall result is not enthusiastic, since there is no statistically significant decrease in breast cancer mortality in the screened population as a whole. And it is always problematic, as Dr Robert points out, to have the results of analyses carried out afterwards, once all the data are in hand, allowing one to "choose" what one wishes to put forward, thus leaving doubt as to the admissibility of the results.
Bernard Duperray[2], in his book "Breast Cancer Screening, the Great Illusion", mentions the Shanghai study where the results found are almost opposite to those of the Mumbai trial: "In a trial carried out in Shanghai from October 1989 to October 1991 on nearly 270,000 women, 130,000 were trained in breast self-examination under medical supervision and compared with a control group (not screened). Cumulative breast cancer mortality rates after 10 to 11 years of follow-up were similar in both groups ...... [3].
To conclude
It is important to keep in mind that this study took place in a very different setting than our Western populations. Initiatives to clinically examine women breast by trained personnel in a setting like Mumbai are likely to reduce the morbidity and stage of cancers for which women may be arriving too late for care. The authors describe the difficulties[4] encountered in carrying out this trial, particularly from the point of view of financing, when Europe at the same time is capable of sacrificing 12 million euros for a study that failed before it even began, and which will not provide any usable information either on overdiagnosis or on the usefulness of mammographic screening.[5]
If this article lacks scientific robustness, and the interest of organized screening by clinical breast examination cannot be formally affirmed, the non-interest of this type of screening by clinical examination is not demonstrated either! A more robust three-arm trial could be imagined, with a 'no screening' arm.
A 'rapid response' to the publication of this study[6] (Ismail Jatoi-Professor and Chief, Division of Surgical Oncology and Endocrine Surgery-University of Texas Health Science Center, San Antonio) is quoted here: ".... the risk of overdiagnosis will increase with the use of more modern screening technology (i.e., tomosynthesis, magnetic resonance imaging), which increases the rate of detection of more occult (non palpable) cancers."
... "Taken together, the results of the Mumbai trial and the CNBSS[7] suggest that a clinical trial randomizing women aged 50 years and older to mammography screening versus clinical breast examination (CBE) screening is now warranted. If such a trial demonstrates that there is no additional benefit to mammography screening beyond what is achievable with CBE screening, then CBE screening should replace screening mammography as the optimal method of breast cancer screening."
Ethically, a randomized clinical trial testing mammographic screening versus clinical screening would be justified, but in France it is unfortunately not possible, since the argument often put forward is that it is unethical to exclude women from mammographic screening. It seems to be considered more ethical to coercively and insistently call women to a radiological screening that has failed....
But the pandemic and future problems of health resource allocation may lead us to rethink this kind of testing around the world, especially for underprivileged populations, rather than furthering disappointing mammographic screening with technologies we know in the western world, which increasingly leads to overdiagnosis.
References
[1] In a scientific study, post hoc analysis (from the Latin post hoc, "after this") consists of statistical analyses that have been specified after the data have been accessed. This usually creates a multiple testing problem because each potential analysis is in fact a statistical test. Multiple testing procedures are sometimes used to compensate, but this is often difficult or impossible to do accurately. Post-hoc analysis that is conducted and interpreted without adequate consideration of this problem is sometimes called "data dredging" by critics because the statistical associations it finds are often wrong. (Wikipédia : https://en.wikipedia.org/wiki/Post_hoc_analysis )
[2] Bernard Duperray "dépistage du cancer du sein, la grande illusion"-éditions Thierry Souccar.
[3] THomas DB, gao Dl et al. Randomized trial of breast self-examination in Shanghai: nal results. Journal of the National Cancer Institute. 2002 Oct 2;94(19):1445-57.
Cox B. Variation in the effectiveness of breast screening by year of follow-up. Journal of the National Cancer Institute. Monographs. 1997;(22):69-72.
Retsky m. New concepts in breast cancer emerge from analyzing clinical data using numerical algorithms. International Journal of Environmental Research and Public Health. 2009 Jan;6(1):329-48.
[7] Miller AB, Wall C, Baines CJ, Sun P, To T, Narod SA. Twenty five year follow-up for breast cancer incidence and mortality of the Canadian National Breast Screening Study: randomised screening trial. BMJ. 2014;348:g366.
b] Explanation of the misleading nature of risk presentations in terms of relative percentage reduction in risk of death. Dr M. Gourmelon
1-Clinical breast examination led to a non-significant 15% reduction in overall breast cancer mortality-
The 15% comes from the following relative calculation:
breast cancer mortality in the screening group 213 deaths, 251 in the control group.
251 -213 = 38
3800/251 = 15,13 %
This is how we obtain a 15% relative reduction in breast cancer mortality.
But what is it in absolute terms?
213 deaths for 75360 women in the screening group.
21300/75360 = 0.2826% is therefore the absolute percentage of deaths of women from breast cancer in the screening group
251 deaths for 76178 women in the control group.
25100/76178 = 0.3295% is the absolute percentage of women who died of breast cancer in the control group.
We therefore have: 0.3295 - 0.2826 = 0.0469% rounded to 0.05% fewer women deaths.
The relative percentage is therefore 15%, and the absolute percentage is 0.05%.
The absolute percentage represents the reduction in mortality of women between the screening group and the control group.
The relative percentage expresses the difference between the total number of deaths in the screening group and the control group, a reduction for a group not for individuals.
However, what is important to know for good information for women is the reduction that they can expect from screening and not how much of a reduction screening brings in the screening group compared to the non-screening group.
But to "promote" screening, it is better to put forward a figure of 15% reduction, which does not concern women directly but which they will interpret as such, than 0.05%, which is the real reduction they can expect by undergoing screening.
This is all the subtlety of presentation of the figures that most readers of the studies will not be aware of, but that the authors, yes. And that the French citizen consultation of 2015 had asked that such presentations are no longer accepted.
2-Second in the same way:
The authors conclude that there is a significant reduction of almost 30% in mortality in women aged ≥ 50 years.
The 30% comes from the following calculation, in the same way:
64 women over 50 years of age who died of breast cancer in the screening group, 93 in the control group.
There is therefore a reduction in breast cancer deaths of : 93-64 = 29
so 2900/93 = 31.18% relative reduction in mortality in women over 50.
But what about the absolute reduction:
64 women died out of 20965 women over 50 in the screening group.
6400/20965 = 0.3053% absolute breast cancer mortality in the screening group
93 women died out of 21909 women over 50 in the control group
9300/21909 = 0,4245 %
or 0.4245-0.3053 = 0.1192
Therefore, in absolute terms, the reduction in mortality of women from breast cancer is 0.12%.
In the same way as before, calculating in absolute % expresses the mortality risk of women over 50 and therefore its reduction, whereas on the other hand, the relative % only expresses a reduction of one group in relation to another: the comparison between the group of screened women and the group of unscreened women and in no case the reduction of risk of women over 50 themselves.
3-Finally, the same is applicable:
A 5% reduction in all-cause mortality was observed in the screening arm compared with the control arm, but was not statistically significant :
11853 all-cause deaths in the control arm
11261 all-cause deaths in the screening arm
11853-11261= 592 fewer deaths.
59200/11853= 4.9945% so 5% fewer deaths between the screening group and the control group but not 5% fewer women who died, because for that you have to calculate in absolute percentage.
This gives:
1126100/75360= 14.94 %
1185300/76178= 15.56 %
15,56-14,94 = 0.62 %
c] Dr Robert's analysis
1. With each post hoc analysis (each subgroup comparison), we give ourselves an additional chance of arriving at a statistically significant result by chance.
Thus, to arrive almost certainly at a statistically significant result, it would be sufficient to create the subgroups at random 100x in a row. With the usual significance level of 0.05, there would be a little more than 99 chances out of 100 that at least 1 of the 100 subgroup comparisons would give (by chance, since the subgroups were formed on a random basis) a p.value <0.05 (in other words, a statistically significant result). (Editor's note: Thus we keep this analysis which seems positive according to the criteria retained by the authors and we can ignore the other 99 studies which appear negative).
Thus the authors do not report 100 post hoc analyses but only 2 (one for the under 50s and one for the over 50s). But, with the 2 post hoc analyses + the main analysis (the one without subgroups), this still gives 3 "tickets" to try to have at least one statistically significant result. The risk of error in the conclusion is therefore no longer 0.05 but about 0.143.
More importantly, it is not known how many post hoc analyses were actually performed. The authors show results for subgroups under 50 and over 50. But in fact, we don't know how many subgroups they tried before arriving at a subgroup with a statistically significant result. Nothing says that they didn't try more than 36 years: no success; then more than 37 years: no success; then more than 38 years: no success; ...; then more than 50 years: p.value = 0.02 we can publish.
The problem is that, in doing so, they would have given themselves 15 "tickets" to have a statistically significant result. The risk of error in the conclusion would therefore no longer be 0.05 but 0.537 (in other words, more than a 1 in 2 chance that the conclusion of a decrease in mortality in women over 50 years of age is due to chance and questionable statistical methodology).
The fact that the authors did post-hoc analyses (no matter how many) proves : - a lack of statistical rigor or knowledge - a lack of objectivity with a strong desire to demonstrate at all costs the effectiveness of screening by palpation (and from then on, one has the right to question the honesty of the study).
2. The study is presented as randomized but in fact it is a cluster randomization (by groups of individuals and not by individuals). The authors state that there are 20 clusters but give no information on the size of the clusters and the heterogeneity of risk factors between the different clusters. It is therefore impossible to know whether or not randomization is sufficient to make the screened and control groups comparable.
To understand the importance of the problem, let's take a caricatured situation:
2 clusters, one high-risk, the other low-risk. In this situation, randomization does not change the comparability of the groups. One will receive the high risk cluster and the other the low risk cluster. Randomization or not, the 2 groups will not be comparable. If the clusters are perfectly identical in terms of risk factors, randomization is unnecessary. No matter how the clusters are assigned to each group, there will be no problem of comparability anyway since all clusters are identical in terms of risk factors. If there are an infinite number of clusters, it does not matter whether they are identical or not in terms of risk, the randomization will balance the distribution of the high and low risk clusters between the 2 groups.
In practice, we are always in an intermediate situation, with a number of clusters > 2 but not infinite and clusters that are not perfectly identical in terms of risk. In order to judge whether or not cluster randomization is likely to produce comparable groups, it is therefore necessary to know both the number of clusters and the heterogeneity between clusters.
3. The way to decide whether or not a death is attributable to breast cancer is rather curious.
Two doctors give their opinion. If the two opinions converge, these identical opinions determine the attribution (OK with that).
If the two opinions differ, a 3rd opinion is requested and the majority opinion determines the attribution. And there is a problem. The majority decision is democratic and well adapted to politics but it is not scientific. If the opinions of the first two doctors differ, the situation is ambiguous.
And it would be more honest not to take these cases into consideration than to want to remove the ambiguity at all costs by a 3rd opinion not necessarily more reliable than the first two.
It is difficult to know how many cases of disagreement there were. There were 17% in one group and 10% in the other where the cause of death could not be attributed; but figures on the frequency of cases where the attribution was made despite a contrary opinion from at least one of the physicians cannot be found. This is crucial information.
At the very least, the robustness of the conclusions should have been checked by a sensitivity study taking into account non-attributions and ambiguities in the attribution of the cause of death (curiously, this was done for the analysis of the staging (analysis of the stage of the cancer at the time of its diagnosis) of cancers and not for the analysis of cancer deaths; in the case of deaths, this removes all reliability from the conclusions)
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