Conditions for Valid Empirical Estimates of Cancer Overdiagnosis in Randomized Trials and Population Studies

Ecological study estimating melanoma overdiagnosis in the USA using the lifetime risk method

OBJECTIVES

To quantify the proportion of melanoma diagnoses (invasive and in situ) in the USA that might be overdiagnosed.

DESIGN

In this ecological study, incidence and mortality data were collected from the Surveillance, Epidemiology and End Results 9 registries database. DevCan software was used to calculate the cumulative lifetime risk of being diagnosed with melanoma between 1975 and 2018, with adjustments made for changes in longevity and risk factors over the study period.

SETTING

USA.

PARTICIPANTS

White American men and women (1975-2018).

MAIN OUTCOME MEASURES

The primary outcome was excess lifetime risk of melanoma diagnosis between 1976 and 2018 (adjusted for year 2018 competing mortality and changes in risk factors), which was inferred as likely overdiagnosis. The secondary outcome was an excess lifetime risk of melanoma diagnosis in each year between 1976 and 2018 (adjusted and unadjusted).

RESULTS

Between 1975 and 2018 the adjusted lifetime risk of being diagnosed with melanoma (invasive and in situ) increased from 3.2% (1 in 31) to 6.4% (1 in 16) among white men, and from 1.6% (1 in 63) to 4.5% (1 in 22) among white women. Over the same period, the adjusted lifetime risk of being diagnosed with melanoma in situ increased from 0.17% (1 in 588) to 2.7% (1 in 37) in white men and 0.08% (1 in 1250) to 2.0% (1 in 50) in white women. An estimated 49.7% of melanomas diagnosed in white men and 64.6% in white women were overdiagnosed in 2018. Among people diagnosed with melanomas in situ, 89.4% of white men and 85.4% of white women were likely overdiagnosed in 2018.

CONCLUSIONS

Melanoma overdiagnosis among white Americans is significant and increasing over time with an estimated 44 000 overdiagnosed in men and 39 000 in women in 2018. A large proportion of overdiagnosed melanomas are in situ cancers, pointing to a potential focus for intervention.

Benefits and Harms of Mammography Screening in 75 + Women to Inform Shared Decision-making: a Simulation Modeling Study

BACKGROUND

Guidelines recommend shared decision-making (SDM) around mammography screening for women ≥ 75 years old.

OBJECTIVE

To use microsimulation modeling to estimate the lifetime benefits and harms of screening women aged 75, 80, and 85 years based on their individual risk factors (family history, breast density, prior biopsy) and comorbidity level to support SDM in clinical practice.

DESIGN, SETTING, AND PARTICIPANTS

We adapted two established Cancer Intervention and Surveillance Modeling Network (CISNET) models to evaluate the remaining lifetime benefits and harms of screening U.S. women born in 1940, at decision ages 75, 80, and 85 years considering their individual risk factors and comorbidity levels. Results were summarized for average- and higher-risk women (defined as having breast cancer family history, heterogeneously dense breasts, and no prior biopsy, 5% of the population).

MAIN OUTCOMES AND MEASURES

Remaining lifetime breast cancers detected, deaths (breast cancer/other causes), false positives, and overdiagnoses for average- and higher-risk women by age and comorbidity level for screening (one or five screens) vs. no screening per 1000 women.

RESULTS

Compared to stopping, one additional screen at 75 years old resulted in six and eight more breast cancers detected (10% overdiagnoses), one and two fewer breast cancer deaths, and 52 and 59 false positives per 1000 average- and higher-risk women without comorbidities, respectively. Five additional screens over 10 years led to 23 and 31 additional breast cancer cases (29-31% overdiagnoses), four and 15 breast cancer deaths avoided, and 238 and 268 false positives per 1000 average- and higher-risk screened women without comorbidities, respectively. Screening women at older ages (80 and 85 years old) and high comorbidity levels led to fewer breast cancer deaths and a higher percentage of overdiagnoses.

CONCLUSIONS

Simulation models show that continuing screening in women ≥ 75 years old results in fewer breast cancer deaths but more false positive tests and overdiagnoses. Together, clinicians and 75 + women may use model output to weigh the benefits and harms of continued screening.

Data-driven overdiagnosis definitions: A scoping review

INTRODUCTION

Adequate methods to promptly translate digital health innovations for improved patient care are essential. Advances in Artificial Intelligence (AI) and Machine Learning (ML) have been sources of digital innovation and hold the promise to revolutionize the way we treat, manage and diagnose patients. Understanding the benefits but also the potential adverse effects of digital health innovations, particularly when these are made available or applied on healthier segments of the population is essential. One of such adverse effects is overdiagnosis.

OBJECTIVE

to comprehensively analyze quantification strategies and data-driven definitions for overdiagnosis reported in the literature.

METHODS

we conducted a scoping systematic review of manuscripts describing quantitative methods to estimate the proportion of overdiagnosed patients.

RESULTS

we identified 46 studies that met our inclusion criteria. They covered a variety of clinical conditions, primarily breast and prostate cancer. Methods to quantify overdiagnosis included both prospective and retrospective methods including randomized clinical trials, and simulations.

CONCLUSION

a variety of methods to quantify overdiagnosis have been published, producing widely diverging results. A standard method to quantify overdiagnosis is needed to allow its mitigation during the rapidly increasing development of new digital diagnostic tools.

Quantification of overdiagnosis in randomised trials of cancer screening: an overview and re-analysis of systematic reviews

The degree of overdiagnosis in common cancer screening trials is uncertain due to inadequate design of trials, varying definition and methods used to estimate overdiagnosis. Therefore, we aimed to quantify the risk of overdiagnosis for the most widely implemented cancer screening programmes and assess the implications of design limitations and biases in cancer screening trials on the estimates of overdiagnosis by conducting an overview and re-analysis of systematic reviews of cancer screening. We searched PubMed and the Cochrane Library from their inception dates to November 29, 2021. Eligible studies included systematic reviews of randomised trials comparing cancer screening interventions to no screening, which reported cancer incidence for both trial arms. We extracted data on study characteristics, cancer incidence and assessed the risk of bias using the Cochrane Collaboration's risk of bias tool. We included 19 trials described in 30 articles for review, reporting results for the following types of screening: mammography for breast cancer, chest X-ray or low-dose CT for lung cancer, alpha-foetoprotein and ultrasound for liver cancer, digital rectal examination, prostate-specific antigen, and transrectal ultrasound for prostate cancer, and CA-125 test and/or ultrasound for ovarian cancer. No trials on screening for melanoma were eligible. Only one trial (5%) had low risk in all bias domains, leading to a post-hoc meta-analysis, excluding trials with high risk of bias in critical domains, finding the extent of overdiagnosis ranged from 17% to 38% across cancer screening programmes. We conclude that there is a significant risk of overdiagnosis in the included randomised trials on cancer screening. We found that trials were generally not designed to estimate overdiagnosis and many trials had high risk of biases that may draw the estimates of overdiagnosis towards the null. In effect, the true extent of overdiagnosis due to cancer screening is likely underestimated.

The influence of postscreening follow-up time and participant characteristics on estimates of overdiagnosis from lung cancer screening trials

We aimed to explore the underlying reasons that estimates of overdiagnosis vary across and within low-dose computed tomography (LDCT) lung cancer screening trials. We conducted a systematic review to identify estimates of overdiagnosis from randomised controlled trials of LDCT screening. We then analysed the association of Ps (the excess incidence of lung cancer as a proportion of screen-detected cases) with postscreening follow-up time using a linear random effects meta-regression model. Separately, we analysed annual Ps estimates from the US National Lung Screening Trial (NLST) and German Lung Cancer Screening Intervention Trial (LUSI) using exponential decay models with asymptotes. We conducted stratified analyses to investigate participant characteristics associated with Ps using the extended follow-up data from NLST. Among 12 overdiagnosis estimates from 8 trials, the postscreening follow-up ranged from 3.8 to 9.3 years, and Ps ranged from -27.0% (ITALUNG, 8.3 years follow-up) to 67.2% (DLCST, 5.0 years follow-up). Across trials, 39.1% of the variation in Ps was explained by postscreening follow-up time. The annual changes in Ps were -3.5% and -3.9% in the NLST and LUSI trials, respectively. Ps was predicted to plateau at 2.2% for NLST and 9.2% for LUSI with hypothetical infinite follow-up. In NLST, Ps increased with age from -14.9% (55-59 years) to 21.7% (70-74 years), and time trends in Ps varied by histological type. The findings suggest that differences in postscreening follow-up time partially explain variation in overdiagnosis estimates across lung cancer screening trials. Estimates of overdiagnosis should be interpreted in the context of postscreening follow-up and population characteristics.

A randomised controlled trial of digital breast tomosynthesis vs digital mammography as primary screening tests: Screening results over subsequent episodes of the Proteus Donna study

Proteus Donna is a randomised controlled trial aimed at prospectively evaluating screening with digital breast tomosynthesis (DBT), including interval cancer detection (ICD) and cancer detection (CD) in the analysis as a cumulative measure over subsequent screening episodes. Consenting women aged 46 to 68 attending the regional Breast Screening Service were randomly assigned to conventional digital mammography (DM, control arm) or DBT in addition to DM (DBT, study arm). At the subsequent round all participants underwent DM. Thirty-six months follow-up allowed for the identification of cancers detected in the subsequent screening and interscreening interval. Relative risk (RR) and 95% confidence interval (95% CI) were computed. Cumulative CD and Nelson-Aalen incidence were analysed over the follow-up period. Between 31 December 2014 and 31 December 2017, 43 022 women were randomised to DM and 30 844 to DBT. At baseline, CD was significantly higher (RR: 1.44, 95% CI: 1.21-1.71) in the study arm. ICD did not differ significantly between the two arms (RR: 0.92, 95% CI: 0.62-1.35). At subsequent screening with DM, the CD was lower (nearly significant) in the study arm (RR: 0.83, 95% CI: 0.65-1.06). Over the follow-up period, the cumulative CD (comprehensive of ICD) was slightly higher in the study arm (RR: 1.15, 95% CI: 1.01-1.31). The Nelson-Aalen cumulative incidence over time remained significantly higher in the study arm for approximately 24 months. Benign lesions detection was higher in the study arm at baseline and lower at subsequent tests. Outcomes are consistent with a lead time gain of DBT compared to DM, with an increase in false positives and moderate overdiagnosis.

Harm-to-Benefit of Three Decades of Prostate Cancer Screening in Black Men

BACKGROUND

Prostate-specific antigen screening has profoundly affected the epidemiology of prostate cancer in the United States. Persistent racial disparities in outcomes for Black men warrant re-examination of the harms of screening relative to its cancer-specific mortality benefits in this population.

METHODS

We estimated overdiagnoses and overtreatment of prostate cancer for men of all races and for Black men 50 to 84 years of age until 2016, the most recent year with treatment data available, using excess incidence relative to 1986 based on the Surveillance, Epidemiology, and End Results registry and U.S. Census data as well as an established microsimulation model of prostate cancer natural history. Combining estimates with plausible mortality benefit, we calculated numbers needed to diagnose (NND) and treat (NNT) to prevent one prostate cancer death.

RESULTS

For men of all races, we estimated 1.5 to 1.9 million (range between estimation approaches) overdiagnosed and 0.9 to 1.5 million overtreated prostate cancers by 2016. Assuming that half of the 270,000 prostate cancer deaths avoided by 2016 were attributable to screening, the NND and the NNT would be 11 to 14 and 7 to 11 for men of all races and 8 to 12 and 5 to 9 for Black men, respectively. Alternative estimates incorporating a lag between incidence and mortality resulted in a NND and a NNT for Black men that reached well into the low single digits.

CONCLUSIONS

Complementary approaches to quantifying overdiagnosis indicate a harm-benefit tradeoff of prostate-specific antigen screening that is more favorable for Black men than for men of all races considered together. Our findings highlight the need to account for the increased value of screening in Black men in clinical guidelines. (Funded by the Patient-Centered Outcomes Research Institute, the National Cancer Institute, the Bristol Myers Squibb Foundation, and the Damon Runyon Cancer Research Foundation.).

Estimation of Breast Cancer Overdiagnosis in a U.S. Breast Screening Cohort

BACKGROUND

Mammography screening can lead to overdiagnosis-that is, screen-detected breast cancer that would not have caused symptoms or signs in the remaining lifetime. There is no consensus about the frequency of breast cancer overdiagnosis.

OBJECTIVE

To estimate the rate of breast cancer overdiagnosis in contemporary mammography practice accounting for the detection of nonprogressive cancer.

DESIGN

Bayesian inference of the natural history of breast cancer using individual screening and diagnosis records, allowing for nonprogressive preclinical cancer. Combination of fitted natural history model with life-table data to predict the rate of overdiagnosis among screen-detected cancer under biennial screening.

SETTING

Breast Cancer Surveillance Consortium (BCSC) facilities.

PARTICIPANTS

Women aged 50 to 74 years at first mammography screen between 2000 and 2018.

MEASUREMENTS

Screening mammograms and screen-detected or interval breast cancer.

RESULTS

The cohort included 35 986 women, 82 677 mammograms, and 718 breast cancer diagnoses. Among all preclinical cancer cases, 4.5% (95% uncertainty interval [UI], 0.1% to 14.8%) were estimated to be nonprogressive. In a program of biennial screening from age 50 to 74 years, 15.4% (UI, 9.4% to 26.5%) of screen-detected cancer cases were estimated to be overdiagnosed, with 6.1% (UI, 0.2% to 20.1%) due to detecting indolent preclinical cancer and 9.3% (UI, 5.5% to 13.5%) due to detecting progressive preclinical cancer in women who would have died of an unrelated cause before clinical diagnosis.

LIMITATIONS

Exclusion of women with first mammography screen outside BCSC.

CONCLUSION

On the basis of an authoritative U.S. population data set, the analysis projected that among biennially screened women aged 50 to 74 years, about 1 in 7 cases of screen-detected cancer is overdiagnosed. This information clarifies the risk for breast cancer overdiagnosis in contemporary screening practice and should facilitate shared and informed decision making about mammography screening.

PRIMARY FUNDING SOURCE

National Cancer Institute.

Assessing the Potential for Patient-led Surveillance After Treatment of Localized Melanoma (MEL-SELF): A Pilot Randomized Clinical Trial

IMPORTANCE

Patient-led surveillance is a promising new model of follow-up care following excision of localized melanoma.

OBJECTIVE

To determine whether patient-led surveillance in patients with prior localized primary cutaneous melanoma is as safe, feasible, and acceptable as clinician-led surveillance.

DESIGN, SETTING, AND PARTICIPANTS

This was a pilot for a randomized clinical trial at 2 specialist-led clinics in metropolitan Sydney, Australia, and a primary care skin cancer clinic managed by general practitioners in metropolitan Newcastle, Australia. The participants were 100 patients who had been treated for localized melanoma, owned a smartphone, had a partner to assist with skin self-examination (SSE), and had been routinely attending scheduled follow-up visits. The study was conducted from November 1, 2018, to January 17, 2020, with analysis performed from September 1, 2020, to November 15, 2020.

INTERVENTION

Participants were randomized (1:1) to 6 months of patient-led surveillance (the intervention comprised usual care plus reminders to perform SSE, patient-performed dermoscopy, teledermatologist assessment, and fast-tracked unscheduled clinic visits) or clinician-led surveillance (the control was usual care).

MAIN OUTCOMES AND MEASURES

The primary outcome was the proportion of eligible and contacted patients who were randomized. Secondary outcomes included patient-reported outcomes (eg, SSE knowledge, attitudes, and practices, psychological outcomes, other health care use) and clinical outcomes (eg, clinic visits, skin surgeries, subsequent new primary or recurrent melanoma).

RESULTS

Of 326 patients who were eligible and contacted, 100 (31%) patients (mean [SD] age, 58.7 [12.0] years; 53 [53%] men) were randomized to patient-led (n = 49) or clinician-led (n = 51) surveillance. Data were available on patient-reported outcomes for 66 participants and on clinical outcomes for 100 participants. Compared with clinician-led surveillance, patient-led surveillance was associated with increased SSE frequency (odds ratio [OR], 3.5; 95% CI, 0.9 to 14.0) and thoroughness (OR, 2.2; 95% CI, 0.8 to 5.7), had no detectable adverse effect on psychological outcomes (fear of cancer recurrence subscale score; mean difference, -1.3; 95% CI, -3.1 to 0.5), and increased clinic visits (risk ratio [RR], 1.5; 95% CI, 1.1 to 2.1), skin lesion excisions (RR, 1.1; 95% CI, 0.6 to 2.0), and subsequent melanoma diagnoses and subsequent melanoma diagnoses (risk difference, 10%; 95% CI, -2% to 23%). New primary melanomas and 1 local recurrence were diagnosed in 8 (16%) of the participants in the intervention group, including 5 (10%) ahead of routinely scheduled visits; and in 3 (6%) of the participants in the control group, with none (0%) ahead of routinely scheduled visits (risk difference, 10%; 95% CI, 2% to 19%).

CONCLUSIONS AND RELEVANCE

This pilot of a randomized clinical trial found that patient-led surveillance after treatment of localized melanoma appears to be safe, feasible, and acceptable. Experiences from this pilot study have prompted improvements to the trial processes for the larger trial of the same intervention.

TRIAL REGISTRATION

http://anzctr.org.au Identifier: ACTRN12616001716459.

Estimating the rate of overdiagnosis with prostate cancer screening: evidence from the Finnish component of the European Randomized Study of Screening for Prostate Cancer

PURPOSE

Screening for prostate cancer may have limited impact on decreasing prostate cancer-related mortality. A major disadvantage is overdiagnosis, whereby lesions are identified that would not have become evident during the man's lifetime if screening had not taken place. The present study aims to estimate the rate of overdiagnosis using Finnish data from the European randomized trial of prostate cancer screening.

METHODS

We used data from 80,149 men randomized to a screening or a control group, distinguishing four birth cohorts. We used the "catch-up method" to identify when the difference in the cumulative incidence of prostate cancer between the screening and control groups had stabilized, implying that the screening has no further effect. We define the overdiagnosis rate to be the relative excess cumulative incidence in the screened group at that point. As an independent method, we also examined the diagnosis rates of T1c tumors as an indicator of early tumors detected by PSA.

RESULTS

The estimates of overdiagnosis rates from the catch-up method using the full period of available follow-up ranged between cohorts from 2.3% to 15.4%, and the T1c analysis gave very similar results.

CONCLUSION

Some overdiagnosis has occurred, but there is uncertainty about its extent. A long follow-up is required to demonstrate the full impact of screening. We evaluated the overdiagnosis rates at a population level, associated with being offered screening, taking account of contamination (screening among the controls). The overall evaluation of screening should incorporate mortality benefit, cost-effectiveness, and quality of life.

Modeled Reductions in Late-stage Cancer with a Multi-Cancer Early Detection Test

BACKGROUND

Cancer is the second leading cause of death globally, with many cases detected at a late stage when prognosis is poor. New technologies enabling multi-cancer early detection (MCED) may make "universal cancer screening" possible. We extend single-cancer models to understand the potential public health effects of adding a MCED test to usual care.

METHODS

We obtained data on stage-specific incidence and survival of all invasive cancers diagnosed in persons aged 50-79 between 2006 and 2015 from the US Surveillance, Epidemiology, and End Results (SEER) program, and combined this with published performance of a MCED test in a state transition model (interception model) to predict diagnostic yield, stage shift, and potential mortality reductions. We model long-term (incident) performance, accou.

Prognostic selection and long-term survival analysis to assess overdiagnosis risk in lung cancer screening randomized trials

OBJECTIVES

Overdiagnosis in low-dose computed tomography randomized screening trials varies from 0 to 67%. The National Lung Screening Trial (extended follow-up) and ITALUNG (Italian Lung Cancer Screening Trial) have reported cumulative incidence estimates at long-term follow-up showing low or no overdiagnosis. The Danish Lung Cancer Screening Trial attributed the high overdiagnosis estimate to a likely selection for risk of the active arm. Here, we applied a method already used in benefit and overdiagnosis assessments to compute the long-term survival rates in the ITALUNG arms in order to confirm incidence-excess method assessment.

METHODS

Subjects in the active arm were invited for four screening rounds, while controls were in usual care. Follow-up was extended to 11.3 years. Kaplan-Meyer 5- and 10-year survivals of "resected and early" (stage I or II and resected) and "unresected or late" (stage III or IV or not resected or unclassified) lung cancer cases were compared between arms.

RESULTS

The updated ITALUNG control arm cumulative incidence rate was lower than in the active arm, but this was not statistically significant (RR: 0.89; 95% CI: 0.67-1.18). A compensatory drop of late cases was observed after baseline screening. The proportion of "resected and early" cases was 38% and 19%, in the active and control arms, respectively. The 10-year survival rates were 64% and 60% in the active and control arms, respectively (p = 0.689). The five-year survival rates for "unresected or late" cases were 10% and 7% in the active and control arms, respectively (p = 0.679).

CONCLUSIONS

This long-term survival analysis, by prognostic categories, concluded against the long-term risk of overdiagnosis and contributed to revealing how screening works.

Lifetime risk of prostate cancer overdiagnosis in Australia: quantifying the risk of overdiagnosis associated with prostate cancer screening in Australia using a novel lifetime risk approach

OBJECTIVES

To quantify the risk of overdiagnosis associated with prostate cancer screening in Australia using a novel lifetime risk approach.

DESIGN

Modelling and validation of the lifetime risk method using publicly available population data.

SETTING

Opportunistic screening for prostate cancer in the Australian population.

PARTICIPANTS

Australian male population (1982-2012).

INTERVENTIONS

Prostate-specific antigen testing for prostate cancer screening.

PRIMARY AND SECONDARY OUTCOME MEASURES

Primary: lifetime risk of overdiagnosis in 2012 (excess lifetime cancer risk adjusted for changing competing mortality); Secondary: lifetime risk of prostate cancer diagnosis (unadjusted and adjusted for competing mortality); Excess lifetime risk of prostate cancer diagnosis (for all years subsequent to 1982).

RESULTS

The lifetime risk of being diagnosed with prostate cancer increased from 6.1% in 1982 (1 in 17) to 19.6% in 2012 (1 in 5). Using 2012 competing mortality rates, the lifetime risk in 1982 was 11.5% (95% CI 11.0% to 12.0%). The excess lifetime risk of prostate cancer in 2012 (adjusted for changing competing mortality) was 8.2% (95% CI 7.6% to 8.7%) (1 in 13). This corresponds to 41% of prostate cancers being overdiagnosed.

CONCLUSIONS

Our estimated rate of overdiagnosis is in agreement with estimates using other methods. This method may be used without the need to adjust for lead times. If annual (cross-sectional) data are used, then it may give valid estimates of overdiagnosis once screening has been established long enough for the benefits from the early detection of non-overdiagnosed cancer at a younger age to be realised in older age groups.

Long-term relationships between screening rates, breast cancer characteristics, and overdiagnosis in US counties, 1975-2009

Effects of mammography screening in the general population are disputed. Screening rates differ greatly between US counties, providing a natural opportunity to investigate effects of screening. We compared mammography screening rates with the types and outcomes of breast cancers diagnosed in US counties. The county screening rate was defined as the proportion of women age ≥40 with ≥1 mammogram in the past 2 years (range, 34-91%). Two periods were analyzed: 1975-2009 (612,941 breast cancer cases, 195 counties) and 1996-2009 (645,057 cases, 211-547 counties). Multiple signs of overdiagnosis were observed: First, breast cancer incidence increased as screening became common. Second, incidence stopped increasing once screening rates stabilized. Third, the increases in incidence were limited to age groups receiving screening. Fourth, the increases were larger in counties where screening became more common. Fifth, the increases were limited to small and early-stage breast cancers (which are consistent with overdiagnosis). Sixth, compensatory reductions in large and advanced-stage breast cancers were much smaller than the increases. Difference-in-differences regression analysis suggested 31% (95% CI: 28-34%) of breast cancers diagnosed in 1996-2009 were overdiagnosed. Screening rates correlated with increased incidence for all hormone receptor statuses, HER2 statuses, and grades. Reductions in breast cancer mortality during 1975-2009 were similar in screened and unscreened age groups. Overall, we found repeated signs that breast cancer overdiagnosis is widespread in the US, but the biological nature of overdiagnosed tumors remains unclear. Mortality benefits of screening, though they may be present and substantial, could not be detected at the population level.

Identification of the Fraction of Indolent Tumors and Associated Overdiagnosis in Breast Cancer Screening Trials

It is generally accepted that some screen-detected breast cancers are overdiagnosed and would not progress to symptomatic cancer if left untreated. However, precise estimates of the fraction of nonprogressive cancers remain elusive. In recognition of the weaknesses of overdiagnosis estimation methods based on excess incidence, there is a need for model-based approaches that accommodate nonprogressive lesions. Here, we present an in-depth analysis of a generalized model of breast cancer natural history that allows for a mixture of progressive and indolent lesions. We provide a formal proof of global structural identifiability of the model and use simulation to identify conditions that allow for parameter estimates that are sufficiently precise and practically actionable. We show that clinical follow-up after the last screening can play a critical role in ensuring adequately precise identification of the fraction of indolent cancers in a stop-screen trial design, and we demonstrate that model misspecification can lead to substantially biased estimates of mean sojourn time. Finally, we illustrate our findings using the example of Canadian National Breast Screening Study 2 (1980-1985) and show that the fraction of indolent cancers is not precisely identifiable. Our findings provide the foundation for extended models that account for both in situ and invasive lesions.

[The development of early cancer detection in Germany]

Cancer is one of the most relevant chronic diseases in the German population, but not all neoplastic entities are eligible for early cancer detection (ECD) programs. In 1971, ECDs were introduced as population-wide screenings for the first time in the catalogue of benefits of the West German statutory health insurance funds. However, the implementation at that time was rarely systematic. Concurrently, a discussion on the perspectives of ECD arose in the former German Democratic Republic, where a structured program was not prepared in the country until the late 1980s.A national cancer plan (NCP) was initiated in 2008 and its area of action #1 was titled "Further development of ECD". In April 2013, the law for the development of early cancer detection and quality assurance by clinical cancer registries was passed, which adopted major suggestions of the NCP. Consequently, the pertinent recommendations of the EU guidelines for the screening of the breast, cervix, and colon-rectum are currently being implemented.Public opinion in Germany with regard to ECDs has changed in recent years from unanimous consent to a rather critical distance. While ineffective and inefficient preventive action is being replaced by quality-assured screening procedures, public discussion about the fundamental reasonability of ECDs is controversial as never before.

Defining, Estimating, and Communicating Overdiagnosis in Cancer Screening

The toll of inadequate health care is well-substantiated, but recognition is mounting that "too much" is also possible. Overdiagnosis represents one harm of too much medicine, but the concept can be confusing: It is often conflated with related harms (such as overtreatment, misclassification, false-positive results, and overdetection) and is difficult to measure because it cannot be directly observed. Because the U.S. Preventive Services Task Force (USPSTF) issues screening recommendations aimed largely at healthy persons, it has a particular interest in understanding harms related to screening, especially but not limited to overdiagnosis. In support of the USPSTF, the authors summarize the knowledge and provide guidance on defining, estimating, and communicating overdiagnosis in cancer screening. To improve consistency, thinking, and reporting about overdiagnosis, they suggest a specific definition. The authors articulate how variation in estimates of overdiagnosis can arise, identify approaches to estimating overdiagnosis, and describe best practices for communicating the potential for harm due to overdiagnosis.

Estimating the frequency of indolent breast cancer in screening trials

Cancer screening can detect cancer that would not have been detected in a patient's lifetime without screening. Standard methods for analyzing screening data do not explicitly account for the possibility that a fraction of tumors may remain latent indefinitely. We extend these methods by representing cancers as a mixture of those that progress to symptoms (progressive) and those that remain latent (indolent). Given sensitivity of the screening test, we derive likelihood expressions to simultaneously estimate (1) the rate of onset of preclinical cancer, (2) the average preclinical duration of progressive cancers, and (3) the fraction of preclinical cancers that are indolent. Simulations demonstrate satisfactory performance of the estimation approach to identify model parameters subject to precise specifications of input parameters and adequate numbers of interval cancers. In application to four breast cancer screening trials, the estimated indolent fraction among preclinical cancers varies between 2% and 35% when assuming 80% test sensitivity and varying specifications for the earliest time that participants could plausibly have developed cancer. We conclude that standard methods for analyzing screening data can be extended to allow some indolent cancers, but accurate estimation depends on correctly specifying key inputs that may be difficult to determine precisely in practice.

Second opinion strategies in breast pathology: a decision analysis addressing over-treatment, under-treatment, and care costs

PURPOSE

To estimate the potential near-term population impact of alternative second opinion breast biopsy pathology interpretation strategies.

METHODS

Decision analysis examining 12-month outcomes of breast biopsy for nine breast pathology interpretation strategies in the U.S. health system. Diagnoses of 115 practicing pathologists in the Breast Pathology Study were compared to reference-standard-consensus diagnoses with and without second opinions. Interpretation strategies were defined by whether a second opinion was sought universally or selectively (e.g., 2nd opinion if invasive). Main outcomes were the expected proportion of concordant breast biopsy diagnoses, the proportion involving over- or under-interpretation, and cost of care in U.S. dollars within one-year of biopsy.

RESULTS

Without a second opinion, 92.2% of biopsies received a concordant diagnosis. Concordance rates increased under all second opinion strategies, and the rate was highest (95.1%) and under-treatment lowest (2.6%) when all biopsies had second opinions. However, over-treatment was lowest when second opinions were sought selectively for initial diagnoses of invasive cancer, DCIS, or atypia (1.8 vs. 4.7% with no 2nd opinions). This strategy also had the lowest projected 12-month care costs ($5.907 billion vs. $6.049 billion with no 2nd opinions).

CONCLUSIONS

Second opinion strategies could lower overall care costs while reducing both over- and under-treatment. The most accurate cost-saving strategy required second opinions for initial diagnoses of invasive cancer, DCIS, or atypia.