Designing cancer screening trials for reduction in late-stage cancer incidence.

Before implementing a biomarker test for early cancer detection into routine clinical care, the test must demonstrate clinical utility, that is, the test results should lead to clinical actions that positively affect patient-relevant outcomes. Unlike therapeutical trials for patients diagnosed with cancer, designing a randomized controlled trial (RCT) to demonstrate the clinical utility of an early detection biomarker with mortality and related endpoints poses unique challenges. The hurdles stem from the prolonged natural progression of the disease and the lack of information regarding the time-varying screening effect on the target asymptomatic population. To facilitate the study design of screening trials, we propose using a generic multistate disease history model and derive model-based effect sizes. The model links key performance metrics of the test, such as sensitivity, to primary endpoints like the incidence of late-stage cancer. It also incorporates the practical implementation of the biomarker-testing program in real-world scenarios. Based on the chronological time scale aligned with RCT, our method allows the assessment of study powers based on key features of the new program, including the test sensitivity, the length of follow-up, and the number and frequency of repeated tests. The calculation tool from the proposed method will enable practitioners to perform realistic and quick evaluations when strategizing screening trials for specific diseases. We use numerical examples based on the National Lung Screening Trial to demonstrate the method.

Long-Term Outcomes in Patients Using Protocol-Directed Active Surveillance for Prostate Cancer.

Importance: Outcomes from protocol-directed active surveillance for favorable-risk prostate cancers are needed to support decision-making. Objective: To characterize the long-term oncological outcomes of patients receiving active surveillance in a multicenter, protocol-directed cohort. Design, Setting, and Participants: The Canary Prostate Active Surveillance Study (PASS) is a prospective cohort study initiated in 2008. A cohort of 2155 men with favorable-risk prostate cancer and no prior treatment were enrolled at 10 North American centers through August 2022. Exposure: Active surveillance for prostate cancer. Main Outcomes and Measures: Cumulative incidence of biopsy grade reclassification, treatment, metastasis, prostate cancer mortality, overall mortality, and recurrence after treatment in patients treated after the first or subsequent surveillance biopsies. Results: Among 2155 patients with localized prostate cancer, the median follow-up was 7.2 years, median age was 63 years, 83% were White, 7% were Black, 90% were diagnosed with grade group 1 cancer, and median prostate-specific antigen (PSA) was 5.2 ng/mL. Ten years after diagnosis, the incidence of biopsy grade reclassification and treatment were 43% (95% CI, 40%-45%) and 49% (95% CI, 47%-52%), respectively. There were 425 and 396 patients treated after confirmatory or subsequent surveillance biopsies (median of 1.5 and 4.6 years after diagnosis, respectively) and the 5-year rates of recurrence were 11% (95% CI, 7%-15%) and 8% (95% CI, 5%-11%), respectively. Progression to metastatic cancer occurred in 21 participants and there were 3 prostate cancer-related deaths. The estimated rates of metastasis or prostate cancer-specific mortality at 10 years after diagnosis were 1.4% (95% CI, 0.7%-2%) and 0.1% (95% CI, 0%-0.4%), respectively; overall mortality in the same time period was 5.1% (95% CI, 3.8%-6.4%). Conclusions and Relevance: In this study, 10 years after diagnosis, 49% of men remained free of progression or treatment, less than 2% developed metastatic disease, and less than 1% died of their disease. Later progression and treatment during surveillance were not associated with worse outcomes. These results demonstrate active surveillance as an effective management strategy for patients diagnosed with favorable-risk prostate cancer.

Dietary Patterns and Risk of Gleason Grade Progression among Men on Active Surveillance for Prostate Cancer: Results from the Canary Prostate Active Surveillance Study.

Modifiable lifestyle factors, such as following a healthy dietary pattern may delay or prevent prostate cancer (PCa) progression. However, few studies have evaluated whether following specific dietary patterns after PCa diagnosis impacts risk of disease progression among men with localized PCa managed by active surveillance (AS). 564 men enrolled in the Canary Prostate Active Surveillance Study, a protocol-driven AS study utilizing a pre-specified prostate-specific antigen monitoring and surveillance biopsy regimen, completed a food frequency questionnaire (FFQ) at enrollment and had ≥ 1 surveillance biopsy during follow-up. FFQs were used to evaluate adherence to the Dietary Guidelines for Americans (Healthy Eating index (HEI))-2015, alternative Mediterranean Diet (aMED), and Dietary Approaches to Stop Hypertension (DASH) dietary patterns. Multivariable-adjusted hazards ratios (HRs) and 95% confidence intervals were estimated using Cox proportional hazards models. During a median follow-up of 7.8 years, 237 men experienced an increase in Gleason score on subsequent biopsy (grade reclassification). Higher HEI-2015, aMED or DASH diet scores after diagnosis were not associated with significant reductions in the risk of grade reclassification during AS. However, these dietary patterns have well-established protective effects on chronic diseases and mortality and remain a prudent choice for men with prostate cancer managed by AS.

Impact of Prostate Health Index Results for Prediction of Biopsy Grade Reclassification During Active Surveillance.

PURPOSE: We assessed whether Prostate Health Index results improve prediction of grade reclassification for men on active surveillance. METHODS AND MATERIALS: We identified men in Canary Prostate Active Surveillance Study with Grade Group 1 cancer. Outcome was grade reclassification to Grade Group 2+ cancer. We considered decision rules to maximize specificity with sensitivity set at 95%. We derived rules based on clinical data (R1) vs clinical data+Prostate Health Index (R3). We considered an "or"-logic rule combining clinical score and Prostate Health Index (R4), and a "2-step" rule using clinical data followed by risk stratification based on Prostate Health Index (R2). Rules were applied to a validation set, where values of R2-R4 vs R1 for specificity and sensitivity were evaluated. RESULTS: We included 1,532 biopsies (n = 610 discovery; n = 922 validation) among 1,142 men. Grade reclassification was seen in 27% of biopsies (23% discovery, 29% validation). Among the discovery set, at 95% sensitivity, R2 yielded highest specificity at 27% vs 17% for R1. In the validation set, R3 had best performance vs R1 with Δsensitivity = -4% and Δspecificity = +6%. There was slight improvement for R3 vs R1 for confirmatory biopsy (AUC 0.745 vs R1 0.724, ΔAUC 0.021, 95% CI 0.002-0.041) but not for subsequent biopsies (ΔAUC -0.012, 95% CI -0.031-0.006). R3 did not have better discrimination vs R1 among the biopsy cohort overall (ΔAUC 0.007, 95% CI -0.007-0.020). CONCLUSIONS: Among active surveillance patients, using Prostate Health Index with clinical data modestly improved prediction of grade reclassification on confirmatory biopsy and did not improve prediction on subsequent biopsies.

Germline mutations in penetrant cancer predisposition genes are rare in men with prostate cancer selecting active surveillance.

BACKGROUND: Pathogenic germline mutations in several rare penetrant cancer predisposition genes are associated with an increased risk of aggressive prostate cancer (PC). Our objectives were to determine the prevalence of pathogenic germline mutations in men with low-risk PC on active surveillance, and assess whether pathogenic germline mutations associate with grade reclassification or adverse pathology, recurrence, or metastases, in men treated after initial surveillance. METHODS: Men prospectively enrolled in the Canary Prostate Active Surveillance Study (PASS) were retrospectively sampled for the study. Germline DNA was sequenced utilizing a hereditary cancer gene panel. Mutations were classified according to the American College of Clinical Genetics and Genomics' guidelines. The association of pathogenic germline mutations with grade reclassification and adverse characteristics was evaluated by weighted Cox proportional hazards modeling and conditional logistic regression, respectively. RESULTS: Overall, 29 of 437 (6.6%) study participants harbored a pathogenic germline mutation of which 19 occurred in a gene involved in DNA repair (4.3%). Eight participants (1.8%) had pathogenic germline mutations in three genes associated with aggressive PC: ATM, BRCA1, and BRCA2. The presence of pathogenic germline mutations in DNA repair genes did not associate with adverse characteristics (univariate analysis HR = 0.87, 95% CI: 0.36-2.06, p = 0.7). The carrier rates of pathogenic germline mutations in ATM, BRCA1, and BRCA2did not differ in men with or without grade reclassification (1.9% vs. 1.8%). CONCLUSION: The frequency of pathogenic germline mutations in penetrant cancer predisposition genes is extremely low in men with PC undergoing active surveillance and pathogenic germline mutations had no apparent association with grade reclassification or adverse characteristics.

Treatment in the absence of disease reclassification among men on active surveillance for prostate cancer.

BACKGROUND: Maintaining men on active surveillance for prostate cancer can be challenging. Although most men who eventually undergo treatment have experienced clinical progression, a smaller subset elects treatment in the absence of disease reclassification. This study sought to understand factors associated with treatment in a large, contemporary, prospective cohort. METHODS: This study identified 1789 men in the Canary Prostate Cancer Active Surveillance Study cohort enrolled as of 2020 with a median follow-up of 5.6 years. Clinical and demographic data as well as information on patient-reported quality of life and urinary symptoms were used in multivariable Cox proportional hazards regression models to identify factors associated with the time to treatment RESULTS: Within 4 years of their diagnosis, 33% of men (95% confidence interval [CI], 30%-35%) underwent treatment, and 10% (95% CI, 9%-12%) were treated in the absence of reclassification. The most significant factor associated with any treatment was an increasing Gleason grade group (adjusted hazard ratio [aHR], 14.5; 95% CI, 11.7-17.9). Urinary quality-of-life scores were associated with treatment without reclassification (aHR comparing "mostly dissatisfied/terrible" with "pleased/mixed," 2.65; 95% CI, 1.54-4.59). In a subset analysis (n = 692), married men, compared with single men, were more likely to undergo treatment in the absence of reclassification (aHR, 2.63; 95% CI, 1.04-6.66). CONCLUSIONS: A substantial number of men with prostate cancer undergo treatment in the absence of clinical changes in their cancers, and quality-of-life changes and marital status may be important factors in these decisions. LAY SUMMARY: This analysis of men on active surveillance for prostate cancer shows that approximately 1 in 10 men will decide to be treated within 4 years of their diagnosis even if their cancer is stable. These choices may be related in part to quality-or-life or spousal concerns.

Evaluating the Outcomes of Active Surveillance in Grade Group 2 Prostate Cancer: Prospective Results from the Canary PASS Cohort.

PURPOSE: Active surveillance (AS) for grade group (GG) 2 patients is not yet well defined. We sought to compare clinical outcomes of men with GG1 and GG2 prostate cancer undergoing AS in a large prospective North American cohort. MATERIALS AND METHODS: Participants were prospectively enrolled in an AS study with protocol-directed followup at 10 centers in the U.S. and Canada. We evaluated time from diagnosis to biopsy grade reclassification and time to treatment. In men treated after initial surveillance, adverse pathology and recurrence were also analyzed. RESULTS: At diagnosis, 154 (9%) had GG2 and 1,574 (91%) had GG1. Five-year reclassification rates were similar between GG2 and GG1 (30% vs 37%, p=0.11). However, more patients with GG2 were treated at 5 years (58% vs 34%, p <0.001) and GG at diagnosis was associated with time to treatment (HR=1.41; p=0.01). Treatment rates were similar in patients who reclassified during AS, but in patients who did not reclassify, those diagnosed with GG2 underwent definitive treatment more often than GG1 (5-year treatment rates 52% and 12%, p <0.0001). In participants who underwent radical prostatectomy after initial surveillance, the adjusted risk of adverse pathology was similar (HR=1.26; p=0.4). Biochemical recurrence within 3 years of treatment for GG2 and GG1 patients was 6% for both groups. CONCLUSIONS: In patients on AS, the rate of definitive treatment is higher after an initial diagnosis of GG2 than GG1. Adverse pathology after radical prostatectomy and short-term biochemical recurrence after definitive treatment were similar between GG2 and GG1.

Effect of Diagnostic Biopsy Practice Location on Grade/Volume Reclassification in Active Surveillance for Prostate Cancer: A Multicenter Analysis from the Canary PASS Cohort.

INTRODUCTION: We analyzed the Canary Prostate Cancer Active Surveillance (PASS) cohort to determine if patients who had diagnostic biopsy at an off-site practice were at higher risk of reclassification than those having their diagnostic biopsy at a PASS site. METHODS: Participants were prospectively enrolled at 10 academic institutions. We included patients with Gleason score 6 at diagnostic biopsy, <34% positive cores and a first surveillance biopsy in a PASS site <2 years after diagnosis. We dichotomized our population based on diagnostic biopsy location (on-PASS site vs off-PASS site) and used multivariable logistic regression to evaluate association with reclassification at first surveillance biopsy after controlling for possible confounders. We used Fisher's exact test to compare rates of definitive prostate cancer treatment by diagnostic biopsy location. RESULTS: Out of 1,648 participants in PASS, 906 met the eligibility criteria and were analyzed. Of 519 men who had off-site diagnostic biopsy, 102 (20%) had grade/volume reclassification compared to 72 (19%) of 399 patients who had on-site diagnostic biopsy. After controlling for potential confounders, location of diagnostic biopsy was not significantly associated with grade/volume reclassification (OR 1.32, IQR 0.91-1.92; p=0.141). Participants with an off-site diagnostic biopsy were more likely to elect definitive treatment than participants with an on-site diagnostic biopsy (17%, IQR 14-20 vs 14%, IQR 10-17 within 1 year after first surveillance biopsy; p <0.01). CONCLUSIONS: In this evaluation of a large multicenter active surveillance cohort, diagnostic biopsy location was not associated with significant differences in grade/volume reclassification on confirmatory biopsy at academic institutions.

Tailoring Intensity of Active Surveillance for Low-Risk Prostate Cancer Based on Individualized Prediction of Risk Stability.

Importance: Active surveillance is increasingly recognized as the preferred standard of care for men with low-risk prostate cancer. However, active surveillance requires repeated assessments, including prostate-specific antigen tests and biopsies that may increase anxiety, risk of complications, and cost. Objective: To identify and validate clinical parameters that can identify men who can safely defer follow-up prostate cancer assessments. Design, Setting, and Participants: The Canary Prostate Active Surveillance Study (PASS) is a multicenter, prospective active surveillance cohort study initiated in July 2008, with ongoing accrual and a median follow-up period of 4.1 years. Men with prostate cancer managed with active surveillance from 9 North American academic medical centers were enrolled. Blood tests and biopsies were conducted on a defined schedule for least 5 years after enrollment. Model validation was performed among men at the University of California, San Francisco (UCSF) who did not enroll in PASS. Men with Gleason grade group 1 prostate cancer diagnosed since 2003 and enrolled in PASS before 2017 with at least 1 confirmatory biopsy after diagnosis were included. A total of 850 men met these criteria and had adequate follow-up. For the UCSF validation study, 533 active surveillance patients meeting the same criteria were identified. Exclusion criteria were treatment within 6 months of diagnosis, diagnosis before 2003, Gleason grade score of at least 2 at diagnosis or first surveillance biopsy, no surveillance biopsy, or missing data. Exposures: Active surveillance for prostate cancer. Main Outcomes and Measures: Time from confirmatory biopsy to reclassification, defined as Gleason grade group 2 or higher on subsequent biopsy. Results: A total of 850 men (median [interquartile range] age, 64 [58-68] years; 774 [91%] White) were included in the PASS cohort. A total of 533 men (median [interquartile range] age, 61 [57-65] years; 422 [79%] White) were included in the UCSF cohort. Parameters predictive of reclassification on multivariable analysis included maximum percent positive cores (hazard ratio [HR], 1.30 [95% CI, 1.09-1.56]; P = .004), history of any negative biopsy after diagnosis (1 vs 0: HR, 0.52 [95% CI, 0.38-0.71]; P < .001 and ≥2 vs 0: HR, 0.18 [95% CI, 0.08-0.4]; P < .001), time since diagnosis (HR, 1.62 [95% CI, 1.28-2.05]; P < .001), body mass index (HR, 1.08 [95% CI, 1.05-1.12]; P < .001), prostate size (HR, 0.40 [95% CI, 0.25-0.62]; P < .001), prostate-specific antigen at diagnosis (HR, 1.51 [95% CI, 1.15-1.98]; P = .003), and prostate-specific antigen kinetics (HR, 1.46 [95% CI, 1.23-1.73]; P < .001). For prediction of nonreclassification at 4 years, the area under the receiver operating curve was 0.70 for the PASS cohort and 0.70 for the UCSF validation cohort. This model achieved a negative predictive value of 0.88 (95% CI, 0.83-0.94) for those in the bottom 25th percentile of risk and of 0.95 (95% CI, 0.89-1.00) for those in the bottom 10th percentile. Conclusions and Relevance: In this study, among men with low-risk prostate cancer, heterogeneity prevailed in risk of subsequent disease reclassification. These findings suggest that active surveillance intensity can be modulated based on an individual's risk parameters and that many men may be safely monitored with a substantially less intensive surveillance regimen.

African American Race is Not Associated with Risk of Reclassification during Active Surveillance: Results from the Canary Prostate Cancer Active Surveillance Study.

PURPOSE: In a large, prospective, multi-institutional active surveillance cohort we evaluated whether African American men are at higher risk for reclassification. MATERIALS AND METHODS: The Canary PASS (Prostate Active Surveillance Study) is a protocol driven, active surveillance cohort with a prespecified prostate specific antigen and surveillance biopsy regimen. Men included in this study had Gleason Grade Group 1 or 2 disease at diagnosis and fewer than 5 years between diagnosis and enrollment, and had undergone 1 or more surveillance biopsies. The reclassification risk, defined as an increase in the Gleason score on subsequent biopsy, was compared between African American and Caucasian American men using Cox proportional hazards models. In the subset of men who underwent delayed prostatectomy the rate of adverse pathology findings, defined as pT3a or greater disease, or Gleason Grade Group 3 or greater, was compared in African American and Caucasian American men. RESULTS: Of the 1,315 men 89 (7%) were African American and 1,226 (93%) were Caucasian American. There was no difference in the treatment rate in African American and Caucasian American men. In multivariate models African American race was not associated with the risk of reclassification (HR 1.16, 95% CI 0.78-1.72). Of the 441 men who underwent prostatectomy after a period of active surveillance the rate of adverse pathology was similar in those who were African American and Caucasian American (46% vs 47%, p=0.99). CONCLUSIONS: Of men on active surveillance who followed a standardized protocol of regular prostate specific antigen testing and biopsy those who were African American were not at increased risk for pathological reclassification while on active surveillance, or for adverse pathology findings at prostatectomy. Active surveillance appears to be an appropriate management strategy for African American men with favorable risk prostate cancer.

Evaluating biomarkers for prognostic enrichment of clinical trials.

BACKGROUND/AIMS: A potential use of biomarkers is to assist in prognostic enrichment of clinical trials, where only patients at relatively higher risk for an outcome of interest are eligible for the trial. We investigated methods for evaluating biomarkers for prognostic enrichment. METHODS: We identified five key considerations when considering a biomarker and a screening threshold for prognostic enrichment: (1) clinical trial sample size, (2) calendar time to enroll the trial, (3) total patient screening costs and the total per-patient trial costs, (4) generalizability of trial results, and (5) ethical evaluation of trial eligibility criteria. Items (1)-(3) are amenable to quantitative analysis. We developed the Biomarker Prognostic Enrichment Tool for evaluating biomarkers for prognostic enrichment at varying levels of screening stringency. RESULTS: We demonstrate that both modestly prognostic and strongly prognostic biomarkers can improve trial metrics using Biomarker Prognostic Enrichment Tool. Biomarker Prognostic Enrichment Tool is available as a webtool at http://prognosticenrichment.com and as a package for the R statistical computing platform. CONCLUSION: In some clinical settings, even biomarkers with modest prognostic performance can be useful for prognostic enrichment. In addition to the quantitative analysis provided by Biomarker Prognostic Enrichment Tool, investigators must consider the generalizability of trial results and evaluate the ethics of trial eligibility criteria.

Tree-based Ensemble Methods For Individualized Treatment Rules.

There is a growing interest in development of statistical methods for personalized medicine or precision medicine, especially for deriving optimal individualized treatment rules (ITRs). An ITR recommends a patient to a treatment based on the patient's characteristics. The common parametric methods for deriving an optimal ITR, which model the clinical endpoint as a function of the patient's characteristics, can have suboptimal performance when the conditional mean model is misspecified. Recent methodology development has cast the problem of deriving optimal ITR under a weighted classification framework. Under this weighted classification framework, we develop a weighted random forests (W-RF) algorithm that derives an optimal ITR nonparametrically. In addition, with the W-RF algorithm, we propose the variable importance measures for quantifying relative relevance of the patient's characteristics to treatment selection, and the out-of-bag estimator for the population average outcome under the estimated optimal ITR. Our proposed methods are evaluated through intensive simulation studies. We illustrate the application of our methods using data from Clinical Antipsychotic Trials of Intervention Effectiveness Alzheimers Disease Study (CATIE-AD).

Assessing the Clinical Impact of Risk Prediction Models With Decision Curves: Guidance for Correct Interpretation and Appropriate Use.

The decision curve is a graphical summary recently proposed for assessing the potential clinical impact of risk prediction biomarkers or risk models for recommending treatment or intervention. It was applied recently in an article in Journal of Clinical Oncology to measure the impact of using a genomic risk model for deciding on adjuvant radiation therapy for prostate cancer treated with radical prostatectomy. We illustrate the use of decision curves for evaluating clinical- and biomarker-based models for predicting a man's risk of prostate cancer, which could be used to guide the decision to biopsy. Decision curves are grounded in a decision-theoretical framework that accounts for both the benefits of intervention and the costs of intervention to a patient who cannot benefit. Decision curves are thus an improvement over purely mathematical measures of performance such as the area under the receiver operating characteristic curve. However, there are challenges in using and interpreting decision curves appropriately. We caution that decision curves cannot be used to identify the optimal risk threshold for recommending intervention. We discuss the use of decision curves for miscalibrated risk models. Finally, we emphasize that a decision curve shows the performance of a risk model in a population in which every patient has the same expected benefit and cost of intervention. If every patient has a personal benefit and cost, then the curves are not useful. If subpopulations have different benefits and costs, subpopulation-specific decision curves should be used. As a companion to this article, we released an R software package called DecisionCurve for making decision curves and related graphics.

Preoperative Use of Methotrexate and the Risk of Early Postoperative Complications in Patients with Inflammatory Bowel Disease.

BACKGROUND: Preoperative immunosuppressive use among patients with Crohn's disease or ulcerative colitis may lead to an increased risk of postoperative complications. There is limited information on the preoperative safety profile of methotrexate (MTX) in inflammatory bowel disease (IBD). METHODS: A retrospective study of patients who underwent abdominal surgery for IBD between 1993 and 2012 was performed and records abstracted, including preoperative use of MTX, azathioprine/6-mercaptopurine, antitumor necrosis factor, and corticosteroids. Early postoperative complications, including death, septic, and nonseptic complications were identified. A meta-analysis was also performed on the use of preoperative MTX in patients with IBD or rheumatoid arthritis. RESULTS: A total of 180 patients with IBD underwent abdominal surgery. A total of 15 patients received MTX either monotherapy or in combination therapy. Total early postoperative complications were identified in 71 (39%) patients, specifically 5 patients on oral MTX. A total of 51 cases (28%) of septic complications and 20 (11%) nonseptic. No significant association between the use of MTX and early postoperative complications was found. The odds ratio (OR) of complications versus no complications associated with MTX was 0.75 (95% CI, 0.25-2.29) and with azathioprine/6-mercaptopurine, OR 1.48 (95% CI, 0.77-2.84). The odds of a septic complication associated with MTX were 0.58 (95% CI, 0.09-3.73), and higher in azathioprine/6-mercaptopurine, OR 3.97 (95% CI, 1.03-15.3). Our meta-analysis also did not reveal an increased risk of postoperative complications in IBD or rheumatoid arthritis on preoperative MTX (OR 0.62, 95% CI, 0.34-1.15). CONCLUSIONS: Preoperative MTX use does not seem to be associated with early postoperative complications in IBD.