Precision Medicine in Active Surveillance for Prostate Cancer: Development of the Canary-Early Detection Research Network Active Surveillance Biopsy Risk Calculator

BACKGROUND

Men on active surveillance (AS) face repeated biopsies. Most biopsy specimens will not show disease progression or change management. Such biopsies do not contribute to patient management and are potentially morbid and costly.

OBJECTIVE

To use a contemporary AS prospective trial to develop a tool to predict AS biopsy outcomes.

DESIGN, SETTING, AND PARTICIPANTS

Biopsy samples (median: 2; range: 2-9 per patient) from 859 men participating in the Canary Prostate Active Surveillance Study and with Gleason 6 prostate cancer (median follow-up: 35.8 mo; range: 3.0-148.7 mo) were analyzed.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Logistic regression was used to predict progression, defined as an increase in Gleason score from ≤6 to ≥7 or increase in percentage of cores positive for cancer from <34% to ≥34%. Fivefold internal cross-validation was performed to evaluate the area under the receiver operating characteristic curve (AUC).

RESULTS AND LIMITATIONS

Statistically significant risk factors for progression on biopsy were prostate-specific antigen (odds ratio [OR]: 1.045; 95% confidence interval [CI], 1.028-1.063), percentage of cores positive for cancer on most recent biopsy (OR: 1.401; 95% CI, 1.301-1.508), and history of at least one prior negative biopsy (OR: 0.524; 95% CI, 0.417-0.659). A multivariable predictive model incorporating these factors plus age and number of months since last biopsy achieved an AUC of 72.4%.

CONCLUSIONS

A combination of readily available clinical measures can stratify patients considering AS prostate biopsy. Risk of progression or upgrade can be estimated and incorporated into clinical practice.

PATIENT SUMMARY

The Canary-Early Detection Research Network Active Surveillance Biopsy Risk Calculator, an online tool, can be used to guide patient decision making regarding follow-up prostate biopsy.

Breast Cancer Screening for Women at Average Risk: 2015 Guideline Update From the American Cancer Society

IMPORTANCE

Breast cancer is a leading cause of premature mortality among US women. Early detection has been shown to be associated with reduced breast cancer morbidity and mortality.

OBJECTIVE

To update the American Cancer Society (ACS) 2003 breast cancer screening guideline for women at average risk for breast cancer.

PROCESS

The ACS commissioned a systematic evidence review of the breast cancer screening literature to inform the update and a supplemental analysis of mammography registry data to address questions related to the screening interval. Formulation of recommendations was based on the quality of the evidence and judgment (incorporating values and preferences) about the balance of benefits and harms.

EVIDENCE SYNTHESIS

Screening mammography in women aged 40 to 69 years is associated with a reduction in breast cancer deaths across a range of study designs, and inferential evidence supports breast cancer screening for women 70 years and older who are in good health. Estimates of the cumulative lifetime risk of false-positive examination results are greater if screening begins at younger ages because of the greater number of mammograms, as well as the higher recall rate in younger women. The quality of the evidence for overdiagnosis is not sufficient to estimate a lifetime risk with confidence. Analysis examining the screening interval demonstrates more favorable tumor characteristics when premenopausal women are screened annually vs biennially. Evidence does not support routine clinical breast examination as a screening method for women at average risk.

RECOMMENDATIONS

The ACS recommends that women with an average risk of breast cancer should undergo regular screening mammography starting at age 45 years (strong recommendation). Women aged 45 to 54 years should be screened annually (qualified recommendation). Women 55 years and older should transition to biennial screening or have the opportunity to continue screening annually (qualified recommendation). Women should have the opportunity to begin annual screening between the ages of 40 and 44 years (qualified recommendation). Women should continue screening mammography as long as their overall health is good and they have a life expectancy of 10 years or longer (qualified recommendation). The ACS does not recommend clinical breast examination for breast cancer screening among average-risk women at any age (qualified recommendation).

CONCLUSIONS AND RELEVANCE

These updated ACS guidelines provide evidence-based recommendations for breast cancer screening for women at average risk of breast cancer. These recommendations should be considered by physicians and women in discussions about breast cancer screening.

Overdetection of recurrence after radical prostatectomy: estimates based on patient and tumor characteristics

PURPOSE

Prostate-specific antigen recurrence (PSA-R) after radical prostatectomy (RP) can occur years before metastasis. This study estimates the chance that an untreated PSA-R would not progress to clinical metastasis within the patient's lifetime, that is, that recurrence is overdetected.

EXPERIMENTAL DESIGN

Times from PSA-R to metastasis were estimated from patients with RP treated at Johns Hopkins University (Baltimore, MD) who did not receive salvage treatment (n = 441) at PSA-R. Times to other-cause death were based on U.S. life tables adjusted to reflect other-cause survival among RP cases in the Surveillance, Epidemiology, and End Results (SEER) registry. We used competing risks simulation to estimate lower bounds on the chance that other-cause death would precede clinical metastasis for patients with disease characteristics at diagnosis based on the Cancer of the Prostate Strategic Urologic Research Endeavor (CaPSURE) database (n = 4,455).

RESULTS

Cumulative incidence of PSA-R in CaPSURE was 13.6% at 5 years and 19.9% at 10 years. The risk of other-cause death among patients with RP in SEER was 60% lower than the age-matched U.S. population. At least 9.1% of patients with PSA-R <5 years after RP and at least 15.6% of patients with PSA-R 5 to 10 years after RP were overdetected. At least 31.4% of patients over the age of 70 years at diagnosis, who recurred <10 years of diagnosis, were overdetected.

CONCLUSIONS

This analysis indicates that PSA-R after RP may be overdetected, with risk depending on patient age and tumor characteristics. The potential for overdetection of recurrence confirms the need for approaches to determine whether and when to initiate salvage therapies.

Predictors of preoperative MRI for breast cancer: differences by data source

AIM

Investigate how the results of predictive models of preoperative MRI for breast cancer change based on available data.

MATERIALS & METHODS

A total of 1919 insured women aged ≥18 with stage 0-III breast cancer diagnosed 2002-2009. Four models were compared using nested multivariable logistic, backwards stepwise regression; model fit was assessed via area under the curve (AUC), R2.

RESULTS

MRI recipients (n = 245) were more recently diagnosed, younger, less comorbid, with higher stage disease. Significant variables included: Model 1/Claims (AUC = 0.76, R2 = 0.10): year, age, location, income; Model 2/Cancer Registry (AUC = 0.78, R2 = 0.12): stage, breast density, imaging indication; Model 3/Medical Record (AUC = 0.80, R2 = 0.13): radiologic recommendations; Model 4/Risk Factor Survey (AUC = 0.81, R2 = 0.14): procedure count.

CONCLUSION

Clinical variables accounted for little of the observed variability compared with claims data.

Prospective quality-of-life outcomes for low-risk prostate cancer: Active surveillance versus radical prostatectomy

BACKGROUND

For patients with low-risk prostate cancer (PCa), active surveillance (AS) may produce oncologic outcomes comparable to those achieved with radical prostatectomy (RP). Health-related quality-of-life (HRQoL) outcomes are important to consider, yet few studies have examined HRQoL among patients with PCa who were managed with AS. In this study, the authors compared longitudinal HRQoL in a prospective, racially diverse, and contemporary cohort of patients who underwent RP or AS for low-risk PCa.

METHODS

Beginning in 2007, HRQoL data from validated questionnaires (the Expanded Prostate Cancer Index Composite and the 36-item RAND Medical Outcomes Study short-form survey) were collected by the Center for Prostate Disease Research in a multicenter national database. Patients aged ≤75 years who were diagnosed with low-risk PCa and elected RP or AS for initial disease management were followed for 3 years. Mean scores were estimated using generalized estimating equations adjusting for baseline HRQoL, demographic characteristics, and clinical patient characteristics.

RESULTS

Of the patients with low-risk PCa, 228 underwent RP, and 77 underwent AS. Multivariable analysis revealed that patients in the RP group had significantly worse sexual function, sexual bother, and urinary function at all time points compared with patients in the AS group. Differences in mental health between groups were below the threshold for clinical significance at 1 year.

CONCLUSIONS

In this study, no differences in mental health outcomes were observed, but urinary and sexual HRQoL were worse for patients who underwent RP compared with those who underwent AS for up to 3 years. These data offer support for the management of low-risk PCa with AS as a means for postponing the morbidity associated with RP without concomitant declines in mental health.

Associations of Obesity with Prostate Cancer Risk Differ Between U.S. African-American and Non-Hispanic White Men: Results from the Selenium and Vitamin E Cancer Prevention Trial

African-American (AA) men have the highest rates of prostate cancer incidence and mortality in the US. Understanding underlying reasons for this disparity could identify preventive interventions important to AA men. PURPOSE: To determine whether the association of obesity with prostate cancer risk differs between AA and non-Hispanic white (NHW) men and whether obesity modifies the excess risk associated with AA race. METHODS: This is a prospective study among 3398 AA and 22673 NHW men who participated in the Selenium and Vitamin E Cancer Prevention Trial (2001–2011). Using Cox regression, we estimated hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) associated with AA and NHW race and body mass index (BMI) [kg/m2] on total, low- (Gleason score &lt;7), and high-grade (Gleason score ≥7) prostate cancer incidence while adjusting for relevant covariates. RESULTS: There were 270, 148, and 88 cases of total, low-, and high-grade prostate cancers among AA men and a corresponding 1453, 898, and 441 cases in NHW men (median follow-up of 5.6 years). BMI was not associated with risk of total cancer among NHW men, but was positively associated with risk among AA men (BMI &lt; 25 kg/m2 vs. ≥35 kg/m2, HR = 1.49; 95% CI, 0.95–2.34; Ptrend = 0.03). Consequently, the risk associated with AA race increased from 28% (HR = 1.28; 95% CI, 0.91–1.80) among men with BMI &lt; 25 kg/m2 to 103% (HR = 2.03; 95% CI, 1.38–2.98) among AA men with BMI≥35 kg/m2 (Ptrend = 0.03). BMI was inversely associated with low-grade prostate cancer risk among NHW men (BMI &lt; 25 kg/m2 vs. ≥35 kg/m2, HR = 0.80; 95% CI, 0.58–1.09; Ptrend = 0.02), but positively associated with risk among AA men (BMI &lt; 25 kg/m2 vs. ≥35 kg/m2, HR = 1.77; 95% CI, 1.14–2.76; Ptrend = 0.05). BMI was positively associated with risk of high-grade prostate cancer in both NHW (BMI &lt; 25 kg/m2 vs. ≥35 kg/m2, HR = 1.33; 95% CI, 0.90–1.97; Ptrend = 0.01) and AA men (BMI &lt; 25 kg/m2 vs. ≥35 kg/m2, HR = 1.81; 95% CI, 0.79–4.11; Ptrend = 0.02), but associations were not significantly different. CONCLUSION: Obesity is more strongly associated with increased prostate cancer risk among AA than NHW men and reducing obesity among AA men could reduce the racial disparity in cancer incidence. Research is needed to test mechanisms underpinning these associations.

Projecting Benefits and Harms of Novel Cancer Screening Biomarkers: A Study of PCA3 and Prostate Cancer

BACKGROUND

New biomarkers for early detection of cancer must pass through several phases of development. Early phases provide information on diagnostic properties but not on population benefits and harms. Prostate cancer antigen 3 (PCA3) is a promising prostate cancer biomarker still in early development. We use simulation modeling to project the impact of adding PCA3 to prostate-specific antigen (PSA) screening on prostate cancer detection and mortality in the United States.

METHODS

We used data from a recent study of PCA3 in men referred for prostate biopsy to extend an existing simulation model of PSA growth, disease progression, and survival. We specified several PSA-PCA3 strategies designed to improve specificity and reduce overdiagnosis. Using these strategies to screen a cohort of men biennially between ages 50 and 74, we projected true- and false-positive tests, overdiagnoses, and lives saved relative to a PSA-based strategy with a cutoff of 4.0 ng/mL for biopsy referral.

RESULTS

We identified several PSA-PCA3 strategies that substantially reduced false-positive tests and overdiagnoses while preserving the majority of lives saved. PCA3>35 for biopsy referral in men with PSA between 4.0 and 10.0 ng/mL retained 85% of lives saved while approximately halving false positives and reducing overdiagnoses by 25%.

CONCLUSIONS

Adding PCA3 to PSA screening can significantly reduce adverse screening outcomes. Strategies can be identified that preserve most of the lives saved relative to PSA-based screening.

IMPACT

Simulation modeling provides advance projections of population outcomes of new screening biomarkers and may help guide early detection research.

Models in the development of clinical practice guidelines

Clinical practice guidelines should be based on the best scientific evidence derived from systematic reviews of primary research. However, these studies often do not provide evidence needed by guideline development groups to evaluate the tradeoffs between benefits and harms. In this article, the authors identify 4 areas where models can bridge the gaps between published evidence and the information needed for guideline development applying new or updated information on disease risk, diagnostic test properties, and treatment efficacy; exploring a more complete array of alternative intervention strategies; assessing benefits and harms over a lifetime horizon; and projecting outcomes for the conditions for which the guideline is intended. The use of modeling as an approach to bridge these gaps (provided that the models are high-quality and adequately validated) is considered. Colorectal and breast cancer screening are used as examples to show the utility of models for these purposes. The authors propose that a modeling study is most useful when strong primary evidence is available to inform the model but critical gaps remain between the evidence and the questions that the guideline group must address. In these cases, model results have a place alongside the findings of systematic reviews to inform health care practice and policy.

A reality check for overdiagnosis estimates associated with breast cancer screening

The frequency of overdiagnosis associated with breast cancer screening is a topic of controversy. Published estimates vary widely, but identifying which estimates are reliable is challenging. In this article we present an approach that provides a check on these estimates. Our approach leverages the close link between overdiagnosis and lead time by identifying the average lead time most consistent with a given overdiagnosis frequency. We consider a high-profile study that suggested that 31% of breast cancers diagnosed in the United States in 2008 were overdiagnosed and show that this corresponds to an average lead time of about nine years among localized cases. Comparing this estimate with the average lead time for invasive, screen-detected breast cancers of 40 months, around which there is a relative consensus, suggests the published estimate of overdiagnosis is excessive. This approach provides a novel way to appraise estimates of overdiagnosis given knowledge of disease natural history.

Tumor marker usage and medical care costs among older early-stage breast cancer survivors

PURPOSE

Although American Society of Clinical Oncology guidelines discourage the use of tumor marker assessment for routine surveillance in nonmetastatic breast cancer, their use in practice is uncertain. Our objective was to determine use of tumor marker tests such as carcinoembryonic antigen and CA 15-3/CA 27.29 and associated Medicare costs in early-stage breast cancer survivors.

METHODS

By using Surveillance, Epidemiology, and End Results-Medicare records for patients diagnosed with early-stage breast cancer between 2001 and 2007, tumor marker usage within 2 years after diagnosis was identified by billing codes. Logistic regression models were used to identify clinical and demographic factors associated with use of tumor markers. To determine impact on costs of care, we used multivariable regression, controlling for other factors known to influence total medical costs.

RESULTS

We identified 39,650 eligible patients. Of these, 16,653 (42%) received at least one tumor marker assessment, averaging 5.7 tests over 2 years, with rates of use per person increasing over time. Factors significantly associated with use included age at diagnosis, diagnosis year, stage at diagnosis, race/ethnicity, geographic region, and urban/rural status. Rates of advanced imaging, but not biopsies, were significantly higher in the assessment group. Medical costs for patients who received at least one test were approximately 29% greater than costs for those who did not, adjusting for other factors.

CONCLUSION

Breast cancer tumor markers are frequently used among women with early-stage disease and are associated with an increase in both diagnostic procedures and total cost of care. A better understanding of factors driving the use of and the potential benefits and harms of surveillance-based tumor marker testing is needed.

Expected population impacts of discontinued prostate-specific antigen screening

BACKGROUND

Prostate-specific antigen (PSA) screening for prostate cancer has high risks of overdiagnosis, particularly among older men, and reports from screening trials indicate that it saves few lives after 11 to 13 years of follow-up. New clinical guidelines recommend against PSA screening for all men or for men aged >70 years, but, to the authors' knowledge, the expected population effects of these guidelines have not been studied to date.

METHODS

Two models of prostate cancer natural history and diagnosis were previously developed using reconstructed PSA screening patterns and prostate cancer incidence in the United States. Assuming a survival benefit of PSA screening consistent with the screening trials, the authors used the models to predict incidence and mortality rates for the period from 2013 through 2025 under continued PSA screening and under discontinued PSA screening for all men or for men aged >70 years.

RESULTS

The models predicted that continuation of recent screening rates will overdiagnose 710,000 to 1,120,000 men (range between models) but will avoid 36,000 to 57,000 cancer deaths over the period 2013 through 2025. Discontinued screening for all men eliminated 100% of overdiagnoses but failed to prevent 100% of avoidable cancer deaths. Continued screening for men aged <70 years eliminated 64% to 66% of overdiagnoses but failed to prevent 36% to 39% of avoidable cancer deaths.

CONCLUSIONS

Discontinuing PSA screening for all men may generate many avoidable cancer deaths. Continuing PSA screening for men aged <70 years could prevent greater than one-half of these avoidable cancer deaths while dramatically reducing overdiagnoses compared with continued PSA screening for all ages.

Personalizing age of cancer screening cessation based on comorbid conditions: model estimates of harms and benefits

BACKGROUND

Harms and benefits of cancer screening depend on age and comorbid conditions, but reliable estimates are lacking.

OBJECTIVE

To estimate the harms and benefits of cancer screening by age and comorbid conditions to inform decisions about screening cessation.

DESIGN

Collaborative modeling with 7 cancer simulation models and common data on average and comorbid condition level-specific life expectancy.

SETTING

U.S. population.

PATIENTS

U.S. cohorts aged 66 to 90 years in 2010 with average health or 1 of 4 comorbid condition levels: none, mild, moderate, or severe.

INTERVENTION

Mammography, prostate-specific antigen testing, or fecal immunochemical testing.

MEASUREMENTS

Lifetime cancer deaths prevented and life-years gained (benefits); false-positive test results and overdiagnosed cancer cases (harms). For each comorbid condition level, the age at which harms and benefits of screening were similar to that for persons with average health having screening at age 74 years.

RESULTS

Screening 1000 women with average life expectancy at age 74 years for breast cancer resulted in 79 to 96 (range across models) false-positive results, 0.5 to 0.8 overdiagnosed cancer cases, and 0.7 to 0.9 prevented cancer deaths. Although absolute numbers of harms and benefits differed across cancer sites, the ages at which to cease screening were consistent across models and cancer sites. For persons with no, mild, moderate, and severe comorbid conditions, screening until ages 76, 74, 72, and 66 years, respectively, resulted in harms and benefits similar to average-health persons.

LIMITATION

Comorbid conditions influenced only life expectancy.

CONCLUSION

Comorbid conditions are an important determinant of harms and benefits of screening. Estimates of screening benefits and harms by comorbid condition can inform discussions between providers and patients about personalizing screening cessation decisions.

PRIMARY FUNDING SOURCE

National Cancer Institute and Centers for Disease Control and Prevention.

Economic return from the Women's Health Initiative estrogen plus progestin clinical trial: a modeling study

BACKGROUND

The findings of the Women's Health Initiative (WHI) estrogen plus progestin (E+P) trial led to a substantial reduction in use of combined hormone therapy (cHT) among postmenopausal women in the United States. The economic effect of this shift has not been evaluated relative to the trial's $260 million cost (2012 U.S. dollars).

OBJECTIVE

To estimate the economic return from the WHI E+P trial.

DESIGN

Decision model to simulate health outcomes for a "WHI scenario" with observed cHT use and a "no-WHI scenario" with cHT use extrapolated from the pretrial period.

DATA SOURCES

Primary analyses of WHI outcomes, peer-reviewed literature, and government sources.

TARGET POPULATION

Postmenopausal women in the United States, aged 50 to 79 years, who did not have a hysterectomy.

TIME HORIZON

2003 to 2012.

PERSPECTIVE

Payer.

INTERVENTION

Combined hormone therapy.

OUTCOME MEASURES

Disease incidence, expenditure, quality-adjusted life-years, and net economic return.

RESULTS OF BASE-CASE ANALYSIS

The WHI scenario resulted in 4.3 million fewer cHT users, 126,000 fewer breast cancer cases, 76,000 fewer cardiovascular disease cases, 263,000 more fractures, 145,000 more quality-adjusted life-years, and expenditure savings of $35.2 billion. The corresponding net economic return of the trial was $37.1 billion ($140 per dollar invested in the trial) at a willingness-to-pay level of $100,000 per quality-adjusted life-year.

RESULTS OF SENSITIVITY ANALYSIS

The 95% CI for the net economic return of the trial was $23.1 to $51.2 billion.

LIMITATION

No evaluation of indirect costs or outcomes beyond 2012.

CONCLUSION

The WHI E+P trial made high-value use of public funds with a substantial return on investment. These results can contribute to discussions about the role of public funding for large, prospective trials with high potential for public health effects.

PRIMARY FUNDING SOURCE

National Heart, Lung, and Blood Institute.

Comparison of survival outcomes among cancer patients treated in and out of clinical trials

BACKGROUND

Clinical trials test the efficacy of a treatment in a select patient population. We examined whether cancer clinical trial patients were similar to nontrial, "real-world" patients with respect to presenting characteristics and survival.

METHODS

We reviewed the SWOG national clinical trials consortium database to identify candidate trials. Demographic factors, stage, and overall survival for patients in the standard arms were compared with nontrial control subjects selected from the Surveillance, Epidemiology, and End Results program. Multivariable survival analyses using Cox regression were conducted. The survival functions from aggregate data across all studies were compared separately by prognosis (≥50% vs <50% average 2-year survival). All statistical tests were two-sided.

RESULTS

We analyzed 21 SWOG studies (11 good prognosis and 10 poor prognosis) comprising 5190 patients enrolled from 1987 to 2007. Trial patients were younger than nontrial patients (P < .001). In multivariable analysis, trial participation was not associated with improved overall survival for all 11 good-prognosis studies but was associated with better survival for nine of 10 poor-prognosis studies (P < .001). The impact of trial participation on overall survival endured for only 1 year.

CONCLUSIONS

Trial participation was associated with better survival in the first year after diagnosis, likely because of eligibility criteria that excluded higher comorbidity patients from trials. Similar survival patterns between trial and nontrial patients after the first year suggest that trial standard arm outcomes are generalizable over the long term and may improve confidence that trial treatment effects will translate to the real-world setting. Reducing eligibility criteria would improve access to clinical trials.

Evaluation of new technologies for cancer control based on population trends in disease incidence and mortality

Cancer interventions often disseminate in the population before evidence of their effectiveness is available. Population disease trends provide a natural experiment for assessing the characteristics of the disease and the potential impact of the intervention. We review models for extracting information from population data for use in economic evaluations of cancer screening interventions. We focus particularly on prostate-specific antigen (PSA) screening for prostate cancer and describe approaches that can be used to project the likely costs and benefits of competing screening policies. Results indicate that the lifetime probability of biopsy-detectable prostate cancer is 33%, the chance of clinical diagnosis without screening is 13%, and the average time from onset to clinical diagnosis is 14 years. Less aggressive screening policies that screen less often and use more conservative criteria (e.g., higher PSA thresholds) for biopsy referral may dramatically reduce PSA screening costs with modest impact on benefit.

Is prostate cancer screening cost-effective? A microsimulation model of prostate-specific antigen-based screening for British Columbia, Canada

Prostate-specific antigen (PSA) screening for prostate cancer may reduce mortality, but it incurs considerable risk of over diagnosis and potential harm to quality of life. Our objective was to evaluate the cost-effectiveness of PSA screening, with and without adjustment for quality of life, for the British Columbia (BC) population. We adapted an existing natural history model using BC incidence, treatment, cost and mortality patterns. The modeled mortality benefit of screening derives from a stage-shift mechanism, assuming mortality reduction consistent with the European Study of Randomized Screening for Prostate Cancer. The model projected outcomes for 40-year-old men under 14 combinations of screening ages and frequencies. Cost and utility estimates were explored with deterministic sensitivity analysis. The incremental cost-effectiveness of regular screening ranged from $36,300/LYG, for screening every four years from ages 55 to 69 years, to $588,300/LYG, for screening every two years from ages 40 to 74 years. The marginal benefits of increasing screening frequency to 2 years or starting screening at age 40 years were small and came at significant cost. After utility adjustment, all screening strategies resulted in a loss of quality-adjusted life years (QALYs); however, this result was very sensitive to utility estimates. Plausible outcomes under a range of screening strategies inform discussion of prostate cancer screening policy in BC and similar jurisdictions. Screening may be cost-effective, but the sensitivity of results to utility values suggests individual preferences for quality versus quantity of life should be a key consideration.

Individualized estimates of overdiagnosis in screen-detected prostate cancer

BACKGROUND

The chance that a prostate cancer detected by screening is overdiagnosed (ie, it would not have been detected in the absence of screening) can vary widely depending on the patient's age and tumor characteristics. The purpose of this study is to use age, Gleason score, and prostate-specific antigen (PSA) level to help inform patients with screen-detected prostate cancers about the chances their cancers were overdiagnosed.

METHODS

A computer microsimulation model of prostate cancer natural history was used to generate virtual life histories in the presence and absence of PSA screening, including an indicator of whether screen-detected cancers are overdiagnosed. A logistic regression model was fit to nonmetastatic patients diagnosed by screening with PSA less than 10 ng/mL, and a nomogram was created to predict the individualized risk of overdiagnosis given age, Gleason score, and PSA at diagnosis.

RESULTS

The calibrated microsimulation model closely reproduces observed incidence trends in the Surveillance, Epidemiology, and End Results registries by age, stage, and Gleason score. The fitted logistic regression predicts risks of overdiagnosis among PSA-detected patients with an area under the curve of 0.75. Chances of overdiagnosis range from 2.9% to 88.1%.

CONCLUSIONS

The chances of overdiagnosis vary considerably by age, Gleason score, and PSA at diagnosis. The overdiagnosis nomogram presents tailored estimates of these risks based on patient and tumor information known at diagnosis and can be used to inform decisions about treating PSA-detected prostate cancers.