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PurposeActive 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 methodsParticipants 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.ResultsAt 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

INTRODUCTION AND OBJECTIVE:The MyProstateScore (MPS) test incorporates prostate cancer antigen 3 (PCA3) and the TMPRSS2:ERG gene fusion (T2:ERG) with serum PSA to better define risk of Grade Group ...

INTRODUCTION AND OBJECTIVE:Maintaining men on active surveillance (AS) for prostate cancer can be challenging. Although most men who eventually undergo treatment have experienced clinical progressi...

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.

BACKGROUND: Biomarker studies on colorectal cancer (CRC) prognosis are limited to pre-diagnostic or pre-operative measures. Post-treatment biomarkers are not well understood for their associations with CRC survival. METHODS: We included 306 eligible incident stage II–III CRC cases from the population-based Seattle Colon Cancer Family Registry. Concentrations of C-reactive protein (CRP), interleukin-6 (IL-6), monocyte chemoattractant protein-1 (MCP-1), adiponectin, and leptin were measured using post-treatment plasma samples. Adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause and CRC-specific mortality were calculated using Cox proportional hazard models. RESULTS: Elevated levels of CRP, IL-6, MCP-1, and adiponectin were significantly associated with a higher risk of all-cause mortality within 10 years post blood draw with HRs (95% CI) of 1.32 (1.10–2.59), 2.72 (2.07–3.56), 1.97 (1.18–3.28) and 1.71 (1.14–2.58), respectively. IL-6 and adiponectin had a dose–response effect (P(trend)

Background Cancer screening is a complex process encompassing risk assessment, the initial screening examination, diagnostic evaluation, and treatment of cancer precursors or early cancers. Metrics that enable comparisons across different screening targets are needed. We present population-based screening metrics for breast, cervical, and colorectal cancers for nine sites participating in the Population-based Research Optimizing Screening through Personalized Regimens consortium. Methods We describe how selected metrics map to a trans-organ conceptual model of the screening process. For each cancer type, we calculated calendar year 2013 metrics for the screen-eligible target population (breast: ages 40–74 years; cervical: ages 21–64 years; colorectal: ages 50–75 years). Metrics for screening participation, timely diagnostic evaluation, and diagnosed cancers in the screened and total populations are presented for the total eligible population and stratified by age group and cancer type. Results The overall screening-eligible populations in 2013 were 305 568 participants for breast, 3 160 128 for cervical, and 2 363 922 for colorectal cancer screening. Being up-to-date for testing was common for all three cancer types: breast (63.5%), cervical (84.6%), and colorectal (77.5%). The percentage of abnormal screens ranged from 10.7% for breast, 4.4% for cervical, and 4.5% for colorectal cancer screening. Abnormal breast screens were followed up diagnostically in almost all (96.8%) cases, and cervical and colorectal were similar (76.2% and 76.3%, respectively). Cancer rates per 1000 screens were 5.66, 0.17, and 1.46 for breast, cervical, and colorectal cancer, respectively. Conclusions Comprehensive assessment of metrics by the Population-based Research Optimizing Screening through Personalized Regimens consortium enabled systematic identification of screening process steps in need of improvement. We encourage widespread use of common metrics to allow interventions to be tested across cancer types and health-care settings.

The MyProstateScore test was validated for improved detection of clinically significant (grade group ≥2) prostate cancer relative to prostate specific antigen based risk calculators. We sought to validate an optimal MyProstateScore threshold for clinical use in ruling out grade group ≥2 cancer in men referred for biopsy.Biopsy naïve men provided post-digital rectal examination urine prior to biopsy. MyProstateScore was calculated using the validated, locked multivariable model including only serum prostate specific antigen, urinary prostate cancer antigen 3 and urinary TMPRSS2:ERG. The MyProstateScore threshold approximating 95% sensitivity for grade group ≥2 cancer was identified in a training cohort, and performance was measured in 2 external validation cohorts. We assessed the 1) overall biopsy referral population and 2) population meeting guideline based testing criteria (ie, prostate specific antigen 3-10, or3 with suspicious digital rectal examination).Validation cohorts were prospectively enrolled from academic (977 patients, median prostate specific antigen 4.5, IQR 3.1-6.0) and community (548, median prostate specific antigen 4.9, IQR 3.7-6.8) settings. In the overall validation population (1,525 patients), 338 men (22%) had grade group ≥2 cancer on biopsy. The MyProstateScore threshold of 10 provided 97% sensitivity and 98% negative predictive value for grade group ≥2 cancer. MyProstateScore testing would have prevented 387 unnecessary biopsies (33%), while missing only 10 grade group ≥2 cancers (3.0%). In 1,242 patients meeting guideline based criteria, MyProstateScore ≤10 provided 96% sensitivity and 97% negative predictive value, and would have prevented 32% of unnecessary biopsies, missing 3.7% of grade group ≥2 cancers.In a large, clinically pertinent biopsy referral population, MyProstateScore ≤10 provided exceptional sensitivity and negative predictive value for ruling out grade group ≥2 cancer. This straightforward secondary testing approach would reduce the use of more costly and invasive procedures after screening with prostate specific antigen.

INTRODUCTION AND OBJECTIVE:The safety of Active Surveillance (AS) for grade group 2 (GG2) patients is debated. We sought to compare clinical outcomes of men with GG1 and GG2 prostate cancer undergo...

PURPOSE The 17-gene Onco type DX Genomic Prostate Score (GPS) test predicts adverse pathology (AP) in patients with low-risk prostate cancer treated with immediate surgery. We evaluated the GPS test as a predictor of outcomes in a multicenter active surveillance cohort. MATERIALS AND METHODS Diagnostic biopsy tissue was obtained from men enrolled at 8 sites in the Canary Prostate Active Surveillance Study. The primary endpoint was AP (Gleason Grade Group [GG] ≥ 3, ≥ pT3a) in men who underwent radical prostatectomy (RP) after initial surveillance. Multivariable regression models for interval-censored data were used to evaluate the association between AP and GPS. Inverse probability of censoring weighting was applied to adjust for informative censoring. Predictiveness curves were used to evaluate how models stratified risk of AP. Association between GPS and time to upgrade on surveillance biopsy was evaluated using Cox proportional hazards models. RESULTS GPS results were obtained for 432 men (median follow-up, 4.6 years); 101 underwent RP after a median 2.1 years of surveillance, and 52 had AP. A total of 167 men (39%) upgraded at a subsequent biopsy. GPS was significantly associated with AP when adjusted for diagnostic GG (hazards ratio [HR]/5 GPS units, 1.18; 95% CI, 1.04 to 1.44; P = .030), but not when also adjusted for prostate-specific antigen density (PSAD; HR, 1.85; 95% CI, 0.99 to 4.19; P = .066). Models containing PSAD and GG, or PSAD, GG, and GPS may stratify risk better than a model with GPS and GG. No association was observed between GPS and subsequent biopsy upgrade ( P = .48). CONCLUSION In our study, the independent association of GPS with AP after initial active surveillance was not statistically significant, and there was no association with upgrading in surveillance biopsy. Adding GPS to a model containing PSAD and diagnostic GG did not significantly improve stratification of risk for AP over the clinical variables alone.

Purpose: Reducing colorectal cancer incidence and mortality through early detection would improve efficacy if targeted. We developed a colorectal cancer risk prediction model incorporating personal, family, genetic, and environmental risk factors to enhance prevention. Methods: A familial risk profile (FRP) was calculated to summarize individuals' risk based on detailed cancer family history (FH), family structure, probabilities of mutation in major colorectal cancer susceptibility genes, and a polygenic component. We developed risk models, including individuals' FRP or binary colorectal cancer FH, and colorectal cancer risk factors collected at enrollment using population-based colorectal cancer cases (N = 4,445) and controls (N = 3,967) recruited by the Colon Cancer Family Registry Cohort (CCFRC). Model validation used CCFRC follow-up data for population-based (N = 12,052) and clinic-based (N = 5,584) relatives with no cancer history at recruitment to assess model calibration [expected/observed rate ratio (E/O)] and discrimination [area under the receiver-operating-characteristic curve (AUC)]. Results: The E/O [95% confidence interval (CI)] for FRP models for population-based relatives were 1.04 (0.74–1.45) for men and 0.86 (0.64–1.20) for women, and for clinic-based relatives were 1.15 (0.87–1.58) for men and 1.04 (0.76–1.45) for women. The age-adjusted AUCs (95% CI) for FRP models for population-based relatives were 0.69 (0.60–0.78) for men and 0.70 (0.62–0.77) for women, and for clinic-based relatives were 0.77 (0.69–0.84) for men and 0.68 (0.60–0.76) for women. The incremental values of AUC for FRP over FH models for population-based relatives were 0.08 (0.01–0.15) for men and 0.10 (0.04–0.16) for women, and for clinic-based relatives were 0.11 (0.05–0.17) for men and 0.11 (0.06–0.17) for women. Conclusions: Both models calibrated well. The FRP-based model provided better risk stratification and risk discrimination than the FH-based model. Impact: Our findings suggest detailed FH may be useful for targeted risk-based screening and clinical management.

BACKGROUND: Choline plays an integral role in one-carbon metabolism in the body, but it is unclear whether genetic polymorphisms are associated with variations in plasma choline and its metabolites. OBJECTIVES: This study aimed to evaluate the association of genetic variants in choline and one-carbon metabolism with plasma choline and its metabolites. METHODS: We analyzed data from 1423 postmenopausal women in a case-control study nested within the Women's Health Initiative Observational Study. Plasma concentrations of choline, betaine, dimethylglycine (DMG), and trimethylamine N-oxide were determined in 12-h fasting blood samples collected at baseline (1993–1998). Candidate and tagging single-nucleotide polymorphisms (SNPs) were genotyped in betaine-homocysteine S-methyltransferase (BHMT), BHMT2, 5,10-methylenetetrahydrofolate reductase (MTHFR), methylenetetrahydrofolate dehydrogenase (NADP+ dependent 1) (MTHFD1), 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR), and 5-methyltetrahydrofolate-homocysteine methyltransferase reductase (MTRR). Linear regression was used to derive percentage difference in plasma concentrations per variant allele, adjusting for confounders, including B-vitamin biomarkers. Potential effect modification by plasma vitamin B-12, vitamin B-6, and folate concentrations and folic-acid fortification periods was examined. RESULTS: The candidate SNP BHMT R239Q (rs3733890) was associated with lower concentrations of plasma betaine and DMG concentrations (−4.00% and −6.75% per variant allele, respectively; both nominal P G, was associated with higher plasma DMG concentration (13.0%; P < 0.0001). Several tagSNPs in these 2 genes were associated with plasma concentrations after correction for multiple comparisons. Vitamin B-12 status was a significant effect modifier of the association between the genetic variant BHMT2 rs626105 A>G and plasma DMG concentration. CONCLUSIONS: Genetic variations in metabolic enzymes were associated with plasma concentrations of choline and its metabolites. Our findings contribute to the knowledge on the variation in blood nutrient concentrations in postmenopausal women.

BACKGROUND: Many patients who are on active surveillance (AS) for prostate cancer will have surveillance prostate needle biopsies (PNBs) without any cancer evident. OBJECTIVE: To define the association between negative surveillance PNBs and risk of reclassification on AS. DESIGN, SETTING, AND PARTICIPANTS: All men were enrolled in the Canary Prostate Active Surveillance Study (PASS) between 2008 and 2016. Men were included if they had Gleason ≤3 + 4 prostate cancer and

Background Diagnosis of Gleason 6 prostate cancer can leave uncertainty about the presence of undetected aggressive disease. Objective To evaluate the utility of a four kallikrein (4K) panel in predicting the presence of high-grade cancer in men on active surveillance. Design, setting, and participants Plasma collected before the first and subsequent surveillance biopsies was assessed for 718 men prospectively enrolled in the multi-institutional Canary PASS trial. Biopsy data were split 2:1 into training and test sets. We developed statistical models that included clinical information and either the 4Kpanel or serum prostate-specific antigen (PSA). Outcome measurements and statistical analysis The endpoint was reclassification to Gleason ≥7. We used receiver operating characteristic (ROC) curve analyses and area under the curve (AUC) to assess discriminatory capacity, and decision curve analysis (DCA) to report clinical net benefit. Results and limitations Significant predictors for reclassification were 4Kpanel (odds ratio [OR] 1.54, 95% confidence interval [CI] 1.31–1.81) or PSA (OR 2.11, 95% CI 1.53–2.91), ≥20% cores positive (OR 2.10, 95% CI 1.33–3.32), two or more prior negative biopsies (OR 0.19, 95% CI 0.04–0.85), prostate volume (OR 0.47, 95% CI 0.31–0.70), and body mass index (OR 1.09, 95% CI 1.04–1.14). ROC curve analysis comparing 4K and base models indicated that the 4Kpanel improved accuracy for predicting reclassification (AUC 0.78 vs 0.74) at the first surveillance biopsy. Both models performed comparably for prediction of reclassification at subsequent biopsies (AUC 0.75 vs 0.76). In DCA, both models showed higher net benefit compared to biopsy-all and biopsy-none strategies. Limitations include the single cohort nature of the study and the small numbers; results should be validated in another cohort before clinical use. Conclusions The 4Kpanel provided incremental value over routine clinical information in predicting high-grade cancer in the first biopsy after diagnosis. The 4Kpanel did not add predictive value to the base model at subsequent surveillance biopsies. Patient summary Active surveillance is a management strategy for many low-grade prostate cancers. Repeat biopsies monitor for previously undetected high-grade cancer. We show that a model with clinical variables, including a panel of four kallikreins, indicates the presence of high-grade cancer before a biopsy is performed.

During active surveillance for localized prostate cancer, the timing of the first surveillance biopsy varies. We analyzed the Canary PASS (Prostate Cancer Active Surveillance Study) to determine biopsy timing influence on rates of prostate cancer adverse reclassification at the first active surveillance biopsy.Of 1,085 participants in PASS, 421 had fewer than 34% of cores involved with cancer and Gleason sum 6 or less, and thereafter underwent on-study active surveillance biopsy. Reclassification was defined as an increase in Gleason sum and/or 34% or more of cores with prostate cancer. First active surveillance biopsy reclassification rates were categorized as less than 8, 8 to 13 and greater than 13 months after diagnosis. Multivariable logistic regression determined association between reclassification and first biopsy timing.Of 421 men, 89 (21.1%) experienced reclassification at the first active surveillance biopsy. Median time from prostate cancer diagnosis to first active surveillance biopsy was 11 months (IQR 7.8-13.8). Reclassification rates at less than 8, 8 to 13 and greater than 13 months were 24%, 19% and 22% (p = 0.65). On multivariable analysis, compared to men biopsied at less than 8 months the OR of reclassification at 8 to 13 and greater than 13 months were 0.88 (95% CI 0.5,1.6) and 0.95 (95% CI 0.5,1.9), respectively. Prostate specific antigen density 0.15 or greater (referent less than 0.15, OR 1.9, 95% CI 1.1, 4.1) and body mass index 35 kg/mTiming of the first active surveillance biopsy was not associated with increased adverse reclassification but prostate specific antigen density and body mass index were. In low risk patients on active surveillance, it may be reasonable to perform the first active surveillance biopsy at a later time, reducing the overall cost and morbidity of active surveillance.

PurposeReducing colorectal cancer (CRC) incidence and mortality through early detection would improve efficacy if targeted. A CRC risk-prediction model incorporating personal, family, genetic and environmental risk factors could enhance prediction.MethodsWe developed risk-prediction models using population-based CRC cases (N=4,445) and controls (N=3,967) recruited by the Colon Cancer Family Registry Cohort (CCFRC). A familial risk profile (FRP) was calculated to summarize individuals’ risk based on their CRC family history, family structure, germline mutation probability in major susceptibility genes, and a polygenic component. Using logistic regression, we developed risk models including individuals’ FRP or a binary CRC family-history (FH), and risk factors collected at recruitment. Model validation used follow-up data for population-(N=12,052) and clinic-based (N=5,584) relatives with no cancer history at recruitment, assessing calibration (E/O) and discrimination (AUC).ResultsThe E/O (95% confidence interval [CI]) for FRP models for population-based relatives were 1.04 (0.74-1.45) and 0.86 (0.64-1.20) for men and women, and for clinic-based relatives 1.15 (0.87-1.58) and 1.04 (0.76-1.45). The age-adjusted AUC (95% CI) for FRP models in population-based relatives were 0.69 (0.60-0.78) and 0.70 (0.62-0.77), and for clinic-based relatives 0.77 (0.69-0.84) and 0.68 (0.60-0.76). The incremental values of AUC (95% CI) for FRP over FH models for population-based relatives were 0.08 (0.01-0.15) and 0.10 (0.04-0.16), and for clinic-based relatives 0.11 (0.05-0.17) and 0.11 (0.06-0.17).ConclusionThe FRP-based model and FH-based model calibrate well in both settings. The FRP-based model provided better risk-prediction and discrimination than the FH-based model. A detailed family history may be useful for targeted risk-based screening and clinical management.

INTRODUCTION AND OBJECTIVES:In active surveillance (AS), disease progression as defined by pathology can only be ascertained at follow-up biopsy. However, clinical factors could also influence the ...

INTRODUCTION AND OBJECTIVES:MRI has been shown to increase detection of clinically significant cancer in the initial diagnosis of prostate cancer. We aim to investigate the ability of multiparametr...

Expert recommendations differ for colorectal cancer screening in the elderly. Recent studies suggest that healthy adults aged75 years may benefit from screening. This study examined screening use and follow-up, and how they varied by health status within age strata, among a large cohort of elderly individuals in community settings.A population-based, longitudinal cohort study was conducted among health plan members aged 65-89 years enrolled during 2011-2012 in three integrated healthcare systems participating in the Population-Based Research Optimizing Screening through Personalized Regimens consortium. Comorbidity measurements used the Charlson index. Analyses, conducted in 2015, comprised descriptive statistics and multivariable modeling that estimated age by comorbidity-specific percentages of patients for two outcomes: colorectal cancer screening uptake and follow-up of abnormal fecal blood tests.Among 846,267 patients, 72% were up-to-date with colorectal cancer screening. Of patients with a positive fecal blood test, 65% received follow-up colonoscopy within 3 months. Likelihood of being up-to-date and receiving timely follow-up was significantly lower for patients aged ≥76 years than their younger counterparts (p0.001). Comorbidity was less influential than age and more strongly related to timely follow-up than being up-to-date. In all age groups, considerable numbers of patients with no/low comorbidity were not up-to-date or did not receive timely follow-up.In three integrated healthcare systems, many older, relatively healthy patients were not screening up-to-date, and some relatively young, healthy patients did not receive timely follow-up. Findings suggest a need for re-evaluating age-based screening guidelines and improving screening completion among the elderly.

Purpose: Active surveillance represents a strategy to address the overtreatment of prostate cancer, yet uncertainty regarding individual patient outcomes remains a concern. We evaluated outcomes in a prospective multicenter study of active surveillance.Materials and Methods: We studied 905 men in the prospective Canary PASS enrolled between 2008 and 2013. We collected clinical data at study entry and at prespecified intervals, and determined associations with adverse reclassification, defined as increased Gleason grade or greater cancer volume on followup biopsy. We also evaluated the relationships of clinical parameters with pathology findings in participants who underwent surgery after a period of active surveillance.Results: At a median followup of 28 months 24% of participants experienced adverse reclassification, of whom 53% underwent treatment while 31% continued on active surveillance. Overall 19% of participants received treatment, 68% with adverse reclassification, while 32% opted for treatment w...

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

Outcomes in patients who enroll in active surveillance programs for prostate cancer while receiving 5α-reductase inhibitors have not been well defined. We sought to determine the association of 5α-reductase inhibitor use with the risk of reclassification in the PASS (Canary Prostate Active Surveillance Study).Participants in the multicenter PASS were enrolled between 2008 and 2016. Study inclusion criteria were current or never 5α-reductase inhibitors use, Gleason score 3 + 4 or less prostate cancer at diagnosis, less than a 34% core involvement ratio at diagnosis and 1 or more surveillance biopsies. Included in study were 1,009 men, including 107 on 5α-reductase inhibitors and 902 who had never received 5α-reductase inhibitors. Reclassification was defined as increase in the Gleason score and/or an increase to 34% or greater in the ratio of biopsy cores positive for cancer. Adverse pathology at prostatectomy was defined as Gleason 4 + 3 or greater and/or nonorgan confined disease (pT3 or N1).On multivariable analysis there was no difference in reclassification between men who had received and those who had never received 5α-reductase inhibitors (HR 0.81, p = 0.31). Patients who had received 5α-reductase inhibitors were less likely to undergo radical prostatectomy (8% vs 18%, p = 0.01) or any definitive treatment (19% vs 24%, p = 0.04). In the 167 participants who underwent radical prostatectomy there was no suggestion of a difference in the rate of adverse pathology findings at prostatectomy between 5α-reductase inhibitor users and nonusers.Continued 5α-reductase inhibitor use after an initial diagnosis of prostate cancer was not associated with the risk of reclassification on active surveillance in men in the PASS cohort.

BACKGROUND: For men on active surveillance for prostate cancer, utility of prostate-specific antigen (PSA) kinetics (PSAk) in predicting pathologic reclassification remains controversial. OBJECTIVE: To develop prediction methods for utilizing serial PSA and evaluate frequency of collection. DESIGN, SETTING, AND PARTICIPANTS: Data were collected from men enrolled in the multicenter Canary Prostate Active Surveillance Study, for whom PSA data were measured and biopsies performed on prespecified schedules. We developed a PSAk parameter based on a linear mixed-effect model (LMEM) that accounted for serial PSA levels. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The association of diagnostic PSA and/or PSAk with time to reclassification (increase in cancer grade and/or volume) was evaluated using multivariable Cox proportional hazards models. RESULTS AND LIMITATIONS: A total of 851 men met the study criteria; 255 (30%) had a reclassification event within 5 yr. Median follow-up was 3.7 yr. After adjusting for prostate size, time since diagnosis, biopsy parameters, and diagnostic PSA, PSAk was a significant predictor of reclassification (hazard ratio for each 0.10 increase in PSAk = 1.6 [95% confidence interval 1.2–2.1, p < 0.001]). The PSAk model improved stratification of risk prediction for the top and bottom deciles of risk over a model without PSAk. Model performance was essentially identical using PSA data measured every 6 mo to those measured every 3 mo. The major limitation is the reliability of reclassification as an end point, although it drives most treatment decisions. CONCLUSIONS: PSAk calculated using an LMEM statistically significantly predicts biopsy reclassification. Models that use repeat PSA measurements outperform a model incorporating only diagnostic PSA. Model performance is similar using PSA assessed every 3 or 6 mo. If validated, these results should inform optimal incorporation of PSA trends into active surveillance protocols and risk calculators. PATIENT SUMMARY: In this report, we looked at whether repeat prostate-specific antigen (PSA) measurements, or PSA kinetics, improve prediction of biopsy outcomes in men using active surveillance to manage localized prostate cancer. We found that in a large multicenter active surveillance cohort, PSA kinetics improves the prediction of surveillance biopsy outcome.

BACKGROUND Investigations of folate-mediated one-carbon metabolism (FOCM) genes and gene-nutrient interactions with respect to colorectal cancer (CRC) risk are limited to candidate polymorphisms and dietary folate. This study comprehensively investigated associations between genetic variants in FOCM and CRC risk and whether the FOCM nutrient status modified these associations. METHODS Two hundred eighty-eight candidate and tagging single-nucleotide polymorphisms (SNPs) in 30 FOCM genes were genotyped for 821 incident CRC case-control matched pairs in the Women's Health Initiative Observational Study cohort. FOCM biomarkers (red blood cell [RBC] folate, plasma folate, pyridoxal-5′-phosphate [PLP], vitamin B12, and homocysteine) and self-reported alcohol consumption were measured at the baseline. Conditional logistic regression was implemented; effect modification was examined on the basis of known enzyme-nutrient relations. RESULTS Statistically significant associations were observed between CRC risk and functionally defined candidate SNPs of methylenetetrahydrofolate dehydrogenase 1 (MTHFD1; K134R), 5-methyltetrahydrofolate-homocysteine methyltransferase reductase (MTRR; P450R), and PR domain containing 2 with ZNF domain (PRDM2; S450N) and a literature candidate SNP of thymidylate synthase (TYMS; g.676789A>T; nominal P

The relationship between folate and colorectal cancer (CRC) risk is unclear. We investigated the association of two biomarkers of folate status, plasma folate and red blood cell (RBC) folate, with CRC risk using a nested case-control design in the Women's Health Initiative Observational Study. Postmenopausal women (n = 93,676) aged 50-79 years were enrolled in the Women's Health Initiative Observational Study (1993-1998). A fasting blood draw and extensive health, dietary and lifestyle data were collected upon enrollment. Through 2008, 988 incident CRC cases were reported and confirmed with medical records adjudication. Cases and controls were matched on age (± 3 years), enrollment date (± 1 year), race/ethnicity, blood draw date (± 6 months) and hysterectomy status. Plasma and RBC folate were determined by radio assay. Folate biomarker values were divided into quartiles, and conditional logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CI) for the associations of folate with total CRC, by tumor site and by stage at diagnosis. Additional analyses examined whether risks varied across time periods corresponding to the United States folic acid fortification policy: prefortification (1994-1995), perifortification (1996-1997) and postfortification (1998). ORs for overall CRC risk comparing Q4 vs. Q1 were 0.91 (95% CI 0.67-1.24) and 0.91 (95% CI 0.67-1.23) for RBC and plasma folate, respectively. There were no changes in risk attributable to food supply fortification. These results do not support an overall association of folate with CRC risk and suggest that folic acid fortification of the US food supply did not alter the associations in these postmenopausal women.

Few studies have examined associations between plasma choline metabolites and risk of colorectal cancer. Therefore, we investigated associations between plasma biomarkers of choline metabolism [choline, betaine, dimethylglycine, and trimethylamine N-oxide (TMAO)] and colorectal cancer risk among postmenopausal women in a case–control study nested within the Women's Health Initiative Observational Study. We selected 835 matched case–control pairs, and cases were further stratified by tumor site (proximal, distal, or rectal) and stage (local/regional or metastatic). Colorectal cancer was assessed by self-report and confirmed by medical records over the mean of 5.2 years of follow-up. Baseline plasma choline metabolites were measured by LC/MS-MS. In multivariable-adjusted conditional logistic regression models, plasma choline tended to be positively associated with rectal cancer risk [OR (95% confidence interval, CI)highest vs. lowest quartile = 2.44 (0.93–6.40); P trend = 0.08], whereas plasma betaine was inversely associated with colorectal cancer overall [0.68 (0.47–0.99); P trend = 0.01] and with local/regional tumors [0.64 (0.42–0.99); P trend = 0.009]. Notably, the plasma betaine:choline ratio was inversely associated with colorectal cancer overall [0.56 (0.39–0.82); P trend = 0.004] as well as with proximal [0.66 (0.41–1.06); P trend = 0.049], rectal [0.27 (0.10–0.78); P trend = 0.02], and local/regional [0.50 (0.33–0.76); P trend = 0.001] tumors. Finally, plasma TMAO, an oxidative derivative of choline produced by intestinal bacteria, was positively associated with rectal cancer [3.38 (1.25–9.16); P trend = 0.02] and with overall colorectal cancer risk among women with lower (vs. higher) plasma vitamin B12 levels (P interaction = 0.003). Collectively, these data suggest that alterations in choline metabolism, which may arise early in disease development, may be associated with higher risk of colorectal cancer. The positive association between plasma TMAO and colorectal cancer risk is consistent with an involvement of the gut microbiome in colorectal cancer pathogenesis. Cancer Res; 74(24); 7442–52. ©2014 AACR.

Background: We hypothesize that prostate specific antigen (PSA), a protein that it is under regulation by androgens, may be differentially expressed in female elite athletes in comparison to control women.Methods: We conducted a cross-sectional study of 106 female athletes and 114 sedentary age-matched controls. Serum from these women was analyzed for complexed prostate specific antigen (cPSA) and free prostate specific antigen (fPSA), by fifth generation assays with limits of detection of around 6 and 140 fg/mL, respectively. A panel of estrogens, androgens and progesterone in the same serum was also quantified by tandem mass spectrometry. Results: Both components of serum PSA (cPSA and fPSA) were lower in the elite athletes vs the control group (P=0.033 and 0.013, respectively). Furthermore, estrone (p=0.003) and estradiol (p=0.004) were significantly lower, and dehydroepiandrosterone (p=0.095) and 5-androstene-3β, 17β-diol (p=0.084) tended to be higher in the athletes vs controls. Oral contraceptive use was similar between groups and significantly associated with increased cPSA and fPSA in athletes (p= 0.046 and 0.009, respectively). PSA fractions were not significantly associated with progesterone changes. The Spearman correlation between cPSA and fPSA in both athletes and controls was 0.75 (P < 0.0001) and 0.64 (P < 0.0001), respectively. Conclusions: Elite athletes have lower complexed and free PSA, higher levels of androgen precursors and lower levels of estrogen in their serum than sedentary control women.Abbreviations: cPSA, complexed PSA; fPSA, free PSA; PCOS, polycystic ovarian syndrome; E1, estrone; E2, estradiol; DHEA, dehydroepiandrosterone, Testo, testosterone; DHT, dihydrotestosterone; PROG, progesterone; Delta 4, androstenedione; Delta 5, androst-5-ene-3β, 17β-diol; BMD, body mineral density; LLOQ, lower limit of quantification; ULOQ, upper limit of quantification; LOD, limit of detection; ACT, α1-antichymotrypsin

Folate-mediated one-carbon metabolism is essential for DNA synthesis, repair, and methylation. Perturbations in one-carbon metabolism have been implicated in increased risk of some cancers and may also affect inflammatory processes. We investigated these interrelated pathways to understand their relation. The objective was to explore associations between inflammation and biomarkers of nutritional status and one-carbon metabolism. In a cross-sectional study in 1976 women selected from the Women's Health Initiative Observational Study, plasma vitamin B-6 [pyridoxal-5'-phosphate (PLP)], plasma vitamin B-12, plasma folate, and RBC folate were measured as nutritional biomarkers; serum C-reactive protein (CRP) and serum amyloid A (SAA) were measured as biomarkers of inflammation; and homocysteine and cysteine were measured as integrated biomarkers of one-carbon metabolism. Student's t, chi-square, and Spearman rank correlations, along with multiple linear regressions, were used to explore relations between biomarkers; additionally, we tested stratification by folic acid fortification period and multivitamin use. With the use of univariate analysis, plasma PLP was the only nutritional biomarker that was modestly significantly correlated with serum CRP and SAA (ρ = -0.22 and -0.12, respectively; P < 0.0001). Homocysteine (μmol/L) showed significant inverse correlations with all nutritional biomarkers (ranging from ρ = -0.30 to ρ = -0.46; all P < 0.0001). With the use of multiple linear regression, plasma PLP, RBC folate, homocysteine, and cysteine were identified as independent predictors of CRP; and PLP, vitamin B-12, RBC folate, and homocysteine were identified as predictors of SAA. When stratified by folic acid fortification period, nutrition-homocysteine correlations were generally weaker in the postfortification period, whereas associations between plasma PLP and serum CRP increased. Biomarkers of inflammation are associated with PLP, RBC folate, and homocysteine in women. The connection between the pathways needs to be further investigated and causality established. The trial is registered at clinicaltrials.gov as NCT00000611.

Few detailed data are available on the wide range of determinants of vitamin D status among postmenopausal women, and it is also unclear whether there may be undiscovered determinants. The objective of this study was to comprehensively evaluate determinants of serum 25-hydroxyvitamin D [25(OH)D] concentrations in a large cohort of postmenopausal women. Data from a subset of the Women's Health Initiative Observational Study were analyzed (50-79 y; n = 3345). Information on diet, lifestyle behaviors, secondhand smoke, use of dietary supplements and medication, chronic diseases, and anthropometry was collected at baseline (1993-1998) and on sun exposure at year 4 follow-up. Linear regression was performed to estimate regression coefficients (β). Significant determinants were total vitamin D intake (food plus supplements per 100 IU/d, β = 2.08), years of supplemental vitamin D use (β = 0.15), total fat intake (grams per day, β = -0.03), smoking status (β = -2.64, current vs. never), regional solar irradiance (β = 6.26, 475-500 vs. 300-325 Langleys), daylight time spent outdoors in summer (β = 5.15, >2 h vs.

Data are very limited on vitamin D and lung cancer prevention in high-risk populations. The authors investigated whether estimated vitamin D intake was associated with lung cancer risk and whether effect modification by vitamin A existed among current/former heavy smokers and workers with occupational exposure to asbestos. A case-cohort study selected 749 incident lung cancers and 679 noncases from the Carotene and Retinol Efficacy Trial (CARET), 1988-2005. The active intervention was supplementation of 30 mg β-carotene + 25,000 IU retinyl palmitate/day. Baseline total intake including both diet (from food frequency questionnaire) and personal supplements (from brand names linked to the labeled potencies) was assessed. Hazard ratios (HRs) were estimated by Cox proportional hazard models. No significant association of total vitamin D intake with lung cancer was observed overall. However, total vitamin D intake ≥600 versus

262 Background: The 17-gene Genomic Prostate Score (GPS) test (scale 0-100) predicts adverse surgical pathology (AP) and recurrence in newly diagnosed low- and intermediate-risk PCa. Studies of the predictive value of the GPS test in men initially managed with AS are limited. Methods: Diagnostic biopsy tissue was obtained from 634 men enrolled at 8 sites in PASS. Time to AP (Gleason Grade Group (GG) ≥3, ≥pT3a, or N1) in men who underwent radical prostatectomy (RP) was the primary endpoint. All diagnostic biopsies and RP specimens were centrally reviewed. Multivariate regression models for interval censored data were used to evaluate the association between time to AP and GPS. Inverse probability of censoring weighting was applied to adjust for informative censoring. Association between GPS and time to Gleason score upgrade on surveillance biopsy was also evaluated using a Cox Proportional Hazards model. Results: GPS results were obtained for 432 men (median follow-up 4.6 [IQR: 2.9-6.2] years); 374 and 58 with GG 1 or 2 cancer, respectively; median PSA density (PSAD) was 0.11 [IQR: 0.08-0.15]; 101 men underwent RP with central pathology after a median of 2.1 [IQR: 1.3-4.3] years surveillance, and 52 (52%) men undergoing RP had AP. 167 men upgraded at a subsequent biopsy. No clinico-pathologic covariates were significantly associated with AP other than PSAD. GPS was significantly associated with time to AP (hazards ratio [HR]/20 GPS units: 1.96 [95% CI = 1.17-4.28]; p = 0.030), when adjusted for diagnostic GG, or for dichotomous PSAD ( < vs ≥ 0.15; HR: 1.83, 95% CI = 1.04-3.62; p = 0.046). GPS was not significantly associated with AP (HR: 1.61, 95% CI = 0.87-2.98; p = 0.12) when adjusted for continuous PSAD. No association, either univariable or multivariable, was observed between GPS and subsequent biopsy upgrade. Conclusions: In a cohort of men on AS, GPS was associated with time to AP when adjusted for diagnostic GG or dichotomous PSAD. GPS was not associated with surveillance biopsy GG upgrading or AP at surgery after adjustment for continuous PSAD, although a trend was seen for AP, suggesting an association may be seen in a larger study.

Author(s): Cheng, Ting-Yuan David; Lacroix, Andrea Z; Beresford, Shirley AA; Goodman, Gary E; Thornquist, Mark D; Zheng, Yingye; Chlebowski, Rowan T; Ho, Gloria YF; Neuhouser, Marian L | Abstract: BackgroundPrior research suggests that vitamin D protects against lung cancer only among certain subgroups.ObjectivesWe investigated whether vitamin D intake was associated with lung cancer and explored whether vitamin A intake modified the association.DesignProspective cohort data from 128,779 postmenopausal women, including 1771 incident lung cancers in the Women's Health Initiative (Clinical Trials and Observational Study) 1993-2010, were analyzed. Twelve percent of women received active intervention (1 g Ca + 400 IU vitamin D3/d) in the Calcium/Vitamin D Trial. Baseline total intake included both dietary intake (from food-frequency questionnaires) and supplement intake (from bottle labels). HRs were estimated by Cox proportional hazard models.ResultsNo significant association was observed overall. Among never smokers, a total vitamin D intake ≥400 IU/d was significantly associated with lower risks of lung cancer (HR: 0.37; 95% CI: 0.18, 0.77 for ≥800 compared with l100 IU/d; P-trend = 0.01). No significant effect modification of total vitamin A intake on the association between total vitamin D intake and lung cancer was found. However, the Calcium/Vitamin D Trial active intervention was significantly associated with a lower lung cancer risk only among women with a vitamin A intake l1000 μg/d retinol activity equivalents (HR: 0.69; 95% CI: 0.50, 0.96; P-interaction = 0.09).ConclusionsVitamin D intake was associated with a lower lung cancer risk in never-smoking, postmenopausal women. Lower vitamin A intake may be important for a beneficial association of 1 g Ca + 400 IU vitamin D3 supplementation with lung cancer. This trial was registered at clinicaltrials.gov as NCT00000611.

Background: Inflammation underlies the etiology of colorectal cancer (CRC). Hyperhomocysteinemia is associated with inflammation and may be a risk marker for CRC. Cysteine is a metabolic product of homocysteine and a precursor of the antioxidant glutathione. It is unknown whether cysteine is associated with CRC. Objective: The objective was to assess the associations between homocysteine and cysteine and CRC incidence in postmenopausal women. Design: Associations between homocysteine and cysteine and incident CRC in the Women’s Health Initiative observational cohort were assessed by using a nested case-control design. Cases and controls (n = 988/group) were matched for age (mean 6 SD age: 67 6 7 y), ethnicity (85.2% white, 8.9% black, 2.2% Hispanic/ Latina, and 3.6% other), hysterectomy status, and date of blood draw. Homocysteine and cysteine were measured by HPLC with postcolumn fluorimetric detection. Results: Multivariate-adjusted ORs (95% CIs) for CRC were 1.46 (1.05, 2.04) for the highest quartile of homocysteine (.9.85 mmol/L) compared with the lowest quartile (#6.74 mmol/L) (P = 0.02) and 0.57 (0.40, 0.82) for the highest quartile of cysteine (.309 mmol/L) compared with the lowest quartile (#260 mmol/L) (P = 0.01). The association with homocysteine was significant for proximal colon tumors (P = 0.008) but not for distal or rectal tumors, whereas the association with cysteine was significant for rectal tumors (P = 0.02), borderline for proximal tumors (P = 0.06), and not significant for distal tumors. The associations with both homocysteine and cysteine were significant for localized tumors (P # 0.01) but not for metastases. Conclusion: High plasma homocysteine is associated with increased risk of CRC, whereas high cysteine is associated with decreased risk. This trial was registered at clinicaltrials.gov as NCT 00000611. Am J Clin Nutr doi: 10.3945/ajcn.112.049932.

Initial studies have investigated the association between inflammation and colorectal cancer (CRC) using C-reactive protein (CRP) as a proinflammatory biomarker and have noted inconsistent results among women. We here report the findings from a large prospective study with repeat measurements of CRP, as well as serum amyloid A (SAA), an additional biomarker of inflammation, and risk of CRC. In the Women's Health Initiative Observational Study, we examined associations of CRP and SAA with CRC using repeat assessments (baseline and 3-year follow-up) among 953 matched case-control pairs for CRP and 966 pairs for SAA. Multivariate-adjusted conditional-logistic regression models were used with two-sided tests of significance. Receiver operating characteristic (ROC) curve analysis assessed their utility as early detection markers. Colon cancer risk (odds ratio [OR] and 95% confidence intervals) among women in the highest quintiles of CRP or SAA compared to those in the lowest quintiles was ORcolon/CRP = 1.37 (0.95-1.97, p-trend = 0.04) and ORcolon/SAA = 1.26 (0.88-1.80, p-trend = 0.10), respectively. Women with elevated concentrations of both CRP and SAA had an increased risk of ORcolon = 1.50 (1.12-2.00, p-value = 0.006) compared to those with low concentrations. No positive associations were observed with rectal cancer and weaker associations for CRC overall. Temporal changes in biomarkers more than 3 years did not predict risk. The area under the 6-month ROC curve for CRP+SAA was 0.62 (95% confidence interval = 0.55-0.68). Elevated inflammatory biomarkers are associated with an increased risk of CRC, mainly colon cancer. Nevertheless, changes in the biomarkers over time do not suggest that they merit consideration as early detection markers for CRC.

Background: Ovarian cancer is the most lethal gynecological malignancy. Our integrated -omics approach to ovarian cancer biomarker discovery has identified kallikrein 6 (KLK6) and folate-receptor 1 (FOLR1) as promising candidates but these markers require further validation. Methods: KLK6, FOLR1, CA125, and HE4 were investigated in three independent serum cohorts with a total of 20 healthy controls, 150 benign controls, and 216 ovarian cancer patients. The serum biomarker levels were determined by ELISA or automated immunoassay. Results: All biomarkers demonstrated elevations in the sera of ovarian cancer patients compared with controls (P < 0.01). Overall, CA125 and HE4 displayed the strongest ability (AUC 0.80 and 0.82, respectively) to identify ovarian cancer patients and the addition of HE4 to CA125 improved the sensitivity from 36% to 67% at a set specificity of 95%. In addition, the combination of HE4 and FOLR1 was a strong predictor of ovarian cancer diagnosis, displaying comparable sensitivity (65%) to the best-performing CA125-based models (67%) at a set specificity of 95%. Conclusions: The markers identified through our integrated -omics approach performed similarly to the clinically approved markers CA125 and HE4. Furthermore, HE4 represents a powerful diagnostic marker for ovarian cancer and should be used more routinely in a clinical setting. Impact: The implications of our study are 2-fold: (i) we have demonstrated the strengths of HE4 alone and in combination with CA125, lending credence to increasing its usage in the clinic; and (ii) we have demonstrated the clinical utility of our integrated -omics approach to identifying novel serum markers with comparable performance to clinical markers. Cancer Epidemiol Biomarkers Prev; 25(9); 1333–40. ©2016 AACR.

BackgroundObesity is a risk factor for incident prostate cancer (PC) as well as risk of disease progression and mortality. We hypothesized that men diagnosed with lower-risk PC and who elected active surveillance (AS) for their cancer management would likely initiate lifestyle changes that lead to weight loss.MethodsPatients were enrolled in the Prostate Active Surveillance Study (PASS), a multicenter prospective biomarker discovery and validation study of men who have chosen AS for their PC. Data from 442 men diagnosed with PC within 1 year of study entry who completed a standard of care 12-month follow-up visit were analyzed. We examined the change in weight and body mass index (BMI) over the first year of study participation.ResultsAfter 1 year on AS, 7.5% (33/442) of patients had lost 5% or more of their on-study weight. The proportion of men who lost 5% or more weight was similar across categories of baseline BMI: normal/underweight (8%), overweight (6%) and obese (10%, χ2 test P=0.44). The results were similar for patients enrolled in the study 1 year or 6 months after diagnosis. By contrast, after 1 year, 7.7% (34/442) of patients had gained >5% of their weight.ConclusionsOnly 7.5% of men with low-risk PC enrolled in AS lost a modest (⩾5%) amount of weight after diagnosis. Given that obesity is related to PC progression and mortality, targeted lifestyle interventions may be effective at this 'teachable moment', as men begin AS for low-risk PC.

Accuracy of risk assessments for clinical outcomes in patients with chronic liver disease has been limited given the nonlinear nature of disease progression. Longitudinal prediction models may more accurately capture this dynamic risk. The aim of this study was to construct accurate models of short- and long-term risk of disease progression in patients with chronic hepatitis C by incorporating longitudinal clinical data. Data from the Hepatitis C Antiviral Long-term Treatment Against Cirrhosis trial were analysed (n = 533 training cohort; n = 517 validation cohort). Outcomes included a composite liver outcome (liver-related death, decompensation, hepatocellular carcinoma (HCC) or liver transplant), decompensation, HCC and overall mortality. Longitudinal models were constructed for risk of outcomes at 1, 3 and 5 years and compared with models using data at baseline only or baseline and a single follow-up time point. A total of 25.1% of patients in the training and 20.8% in the validation cohort had an outcome during a median follow-up of 6.5 years (range 0.5-9.2). The most important predictors were as follows: albumin, aspartate aminotransferase/alanine aminotransferase ratio, bilirubin, alpha-fetoprotein and platelets. Longitudinal models outperformed baseline models with higher true-positive rates and negative predictive values. The areas under the receiver-operating characteristic curve for the composite longitudinal model were 0.89 (0.80-0.96), 0.83 (0.76-0.88) and 0.81 (0.75-0.87) for 1-, 3-, and 5-year risk prediction, respectively. Model performance was retained for decompensation and overall mortality but not HCC. Longitudinal prediction models provide accurate risk assessments and identify patients in need of intensive monitoring and care.

Background: To reduce colorectal cancer mortality, positive fecal blood tests must be followed by colonoscopy. Methods: We identified 62,384 individuals ages 50 to 89 years with a positive fecal blood test between January 1, 2011 and December 31, 2012 in four health care systems within the Population-Based Research Optimizing Screening through Personalized Regimens (PROSPR) consortium. We estimated the probability of follow-up colonoscopy and 95% confidence intervals (CI) using the Kaplan–Meier method. Overall differences in cumulative incidence of follow-up across health care systems were assessed with the log-rank test. HRs and 95% CIs were estimated from multivariate Cox proportional hazards models. Results: Most patients who received a colonoscopy did so within 6 months of their positive fecal blood test, although follow-up rates varied across health care systems (P Conclusion: Individual characteristics and health care system were associated with colonoscopy after positive fecal blood tests. Patterns were consistent across health care systems, but proportions of patients receiving follow-up varied. These findings suggest that there is room to improve follow-up of positive colorectal cancer screening tests. Impact: Understanding the timing of colonoscopy after positive fecal blood tests and characteristics associated with lack of follow-up may inform future efforts to improve follow-up. Cancer Epidemiol Biomarkers Prev; 25(2); 344–50. ©2016 AACR.

Background: Non-steroidal anti-inflammatory drugs (NSAIDs) and hormone therapy (HT) independently decrease the risk of colorectal cancer. However, their role in altering survival after a colorectal cancer diagnosis is not well established. Methods: We examined the association between the use of these common medications before diagnosis and colorectal cancer survival among women in western Washington State diagnosed with incident colorectal cancer from 1997 to 2002. Cases were ascertained using the Surveillance, Epidemiology and End Results cancer registry; mortality follow-up was completed through linkages to the National Death Index. Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results: We observed no overall association between colorectal cancer survival and pre-diagnostic NSAID use. However, when stratified by tumour sub-site, NSAID use was associated with a reduced risk of colorectal cancer mortality for women diagnosed with proximal (HR=0.55; 95% CI: 0.32–0.92), but not distal or rectal (HR=1.32; 95% CI: 0.83–2.10) tumours. The usage of HT was not associated with colorectal cancer survival overall or by tumour sub-site. Conclusion: Usage of NSAIDs before diagnosis may be associated with improved colorectal cancer survival among women diagnosed with proximal tumours. The usage of HT does not appear to have a function in altering colorectal cancer mortality.

Background: Supplement use among cancer patients is high, and folic acid intake in particular may adversely affect the progression of colorectal cancer. Few studies have evaluated the use of folic acid–containing supplements (FAS) and its predictors in colorectal cancer patients. Objective: To assess the use of FAS, change in use, and its predictors after colorectal cancer diagnosis. Design: We used logistic regression models to investigate predictors of FAS use and its initiation after colorectal cancer diagnosis in 1,092 patients recruited through the Colon Cancer Family Registry. Results: The prevalence of FAS use was 35.4% before and 55.1% after colorectal cancer diagnosis (P = 0.004). Women were more likely than men to use FAS after diagnosis [odds ratio (OR), 1.47; 95% confidence interval (95% CI), 1.14-1.89], as were those consuming more fruit (Ptrend < 0.0001) or vegetables (Ptrend = 0.001), and U.S. residents (P < 0.0001). Less likely to use FAS after diagnosis were nonwhite patients (OR, 0.66; 95% CI, 0.45-0.97), current smokers (OR, 0.67; 95% CI, 0.46-0.96), and those with higher meat intake (Ptrend = 0.03). Predictors of FAS initiation after diagnosis were generally similar to those of FAS use after diagnosis, although associations with race and vegetable intake were weaker and those with exercise stronger. Conclusions: Our analysis showed substantial increases in the use of FAS after diagnosis with colorectal cancer, with use or initiation more likely among women, Caucasians, U.S. residents, and those with a health-promoting life-style. Impact: Studies of cancer prognosis that rely on prediagnostic exposure information may result in substantial misclassification. Cancer Epidemiol Biomarkers Prev; 19(8); 2023–34. ©2010 AACR.

140 Background: Active surveillance is endorsed as the preferred management strategy for most men with low-risk prostate cancer. However, nearly all active surveillance protocols entail prostate specific antigen (PSA) testing every 3-6 months, and prostate biopsies every 1-2 years. For many men with indolent tumors, this regimen is overly intense, and exposes men to the discomfort, risks, and costs of repeated biopsies. We aimed to determine if some men can be safely selected for a less intense surveillance regimen by predicting the probability of non-reclassification over the next 4 years of surveillance. Methods: Data were collected from men in the multicenter Canary Prostate Active Surveillance Study (PASS), in which PSAs are collected q3 months and biopsies performed 12 months of diagnosis and then every 2 years. For inclusion in this study, men had to have undergone ≤ 1 follow up biopsy, and have Gleason grade group 1 at diagnosis. Reclassification was defined as increase in Gleason grade group on subsequent biopsy; those without reclassification were censored at last study contact, treatment or 2 years after last biopsy. A dynamic risk prediction model based on a Cox regression with robust variance estimates was used to construct and test a model predicting non-reclassification. Results: Of 1082 men included, 362 (33%) reclassified and the remaining were censored. The final regression model included percent of biopsy cores involved, prior biopsy history, time since diagnosis, BMI, prostate size, diagnostic PSA, and PSAk (a measure of PSA kinetics). This dynamic risk prediction model was assessed at a measurement time of 1 year after diagnosis, predicting risk of reclassification at 4 years. Men at lowest and highest deciles of this model-based risk faced 6% (95%CI 0-12%) and 73% (55-84%) risks of reclassification within 5 years. For at least 10% of the men in the cohort, the negative predictive value (NPV) for reclassification was 95% or higher. Conclusions: A substantial proportion of men with low-risk prostate cancer can safely be followed with a de-intensified active surveillance protocol, which would improve both the tolerability and cost-effectiveness of this management strategy.

Currently, there are no effective biomarkers for ovarian cancer prognosis or prediction of therapeutic response. The objective of this study was to examine a panel of 10 serum biochemical parameters for their ability to predict response to chemotherapy, progression and survival of ovarian cancer patients. Sera from ovarian cancer patients were collected prior and during chemotherapy and were analysed by enzyme-linked immunosorbent assay for CA125, kallikreins 5, 6, 7, 8, 10 and 11, B7-H4, regenerating protein IV and Spondin-2. The odds ratio and hazard ratio and their 95% confidence interval (95% CI) were calculated. Time-dependent receiver-operating characteristic (ROC) curves were utilised to evaluate the prognostic performance of the biomarkers. The levels of several markers at baseline (c(0)), or after the first chemotherapy cycle (rc(1)), predicted chemotherapy response and overall or progression-free survival in univariate analysis. A multiparametric model (c(0) of CA125, KLK5, KLK7 and rc(1) of CA125) provided predictive accuracy with area under the ROC curve (AUC) of 0.82 (0.62 after correction for overfitting). Another marker combination (c(0) of KLK7, KLK10, B7-H4, Spondin-2) was useful in predicting short-term (1-year) survival with an AUC of 0.89 (0.74 after correction for overfitting). All markers examined, except KLK7 and regenerating protein IV, were powerful predictors of time to progression (TTP) among chemotherapy responders. Individual and panels of biomarkers from the kallikrein family (and other families) can predict response to chemotherapy, overall survival, short-term (1-year) survival, progression-free survival and TTP of ovarian cancer patients treated with chemotherapy.

Purpose: Our goal was to examine a panel of 11 biochemical variables, measured in cytosolic extracts of ovarian tissues (normal, benign, and malignant) by quantitative ELISAs for their ability to diagnose, prognose, and predict response to chemotherapy of ovarian cancer patients. Experimental Design: Eleven proteins were measured (9 kallikreins, B7-H4, and CA125) in cytosolic extracts of 259 ovarian tumor tissues, 50 tissues from benign conditions, 35 normal tissues, and 44 tissues from nonovarian tumors that metastasized to the ovary. Odds ratios and hazard ratios and their 95% confidence interval were calculated. Time-dependent receiver operating characteristic curves for censored survival data were used to evaluate the performance of the biomarkers. Resampling was used to validate the performance. Results: Most biomarkers effectively separated cancer from noncancer groups. A composite marker provided an area under the curve of 0.97 (95% confidence interval, 0.95-0.99) for discriminating normal and cancer groups. Univariately, hK5 and hK6 were positively associated with progression. After adjusting for clinical variables in multivariate analysis, both hK10 and hK11 significantly predicted time to progression. Increasing levels of hK13 were associated with chemotherapy response, and the predictive power of hK13 to chemotherapy response was improved by a panel of five biomarkers. Conclusions: The evidence shows that a group of kallikreins and multiparametric combinations with other biomarkers and clinical variables can significantly assist with ovarian cancer classification, prognosis, and response to platinum-based chemotherapy. In particular, we developed a multiparametric strategy for predicting ovarian cancer response to chemotherapy, comprising several biomarkers and clinical features.

Current users of postmenopausal hormones (PMH) have ∼30% to 40% lower risk of colorectal cancer (CRC), although associations with specific types of hormones have been inconsistent. Further, it is not clear whether some tumor types have a different risk. We conducted a case-control study to examine the relationship between PMH and CRC. Cases (n = 1,004), ages 50 to 74 years, were identified from the Surveillance Epidemiology and End Results registry in Washington from 1998 to 2002; controls (n = 1,062) were randomly selected from population lists. Case tissue samples were obtained for microsatellite instability (MSI) analyses. Interviews collected risk-factor data for CRC, including detailed information on PMH. Multivariable logistic regression models estimated odds ratios (OR) and 95% confidence intervals (95% CI). Current use of any PMH was associated with a 20% reduction in CRC risk (95% CI 0.6–0.9). This reduction in risk was limited to women who had taken estrogen plus progestin (EP) preparations only (OR = 0.6, 95% CI 0.5–0.9); there was no association with estrogen-only (E alone) use (OR = 0.9, 95% CI 0.7–1.1). For women with MSI-low or MSI-stable tumors, there was a statistically significant 40% reduction in CRC risk associated with EP use (95% CI 0.4–0.9); there was no clear association with MSI-high tumors. EP use was associated with a decreased risk of CRC; however, there seemed to be no association with E alone data that are consistent with the recent Women's Health Initiative findings. Progestin may enhance the estrogenic effect of conjugated estrogen so the combination may be more biologically active in the colon than E alone. [Cancer Res 2007;67(15):7534–9]

INTRODUCTION AND OBJECTIVES: Active surveillance (AS) is gaining acceptance for men with low risk prostate cancer (PCa) to prevent over-treatment related morbidity. Variability exists regarding the timing of the confirmatory biopsy (CBx) after diagnostic biopsy (DBx) in AS protocols. We analyze the Prostate Cancer Active Surveillance (PASS) cohort, determining timing and rates of PCa adverse reclassification (henceforth called reclassification) on CBx. METHODS: Men (N1⁄4422) with low risk PCA on AS were selected from the multicenter PASS cohort (1,067 screened). Criteria included enrollment within 1 year of DBx, receipt of CBx after enrollment, DBx with 1⁄47 or to >1⁄434% cores involved. The PASS protocol requires a CBx within the first 6-12 months of DBx. The time interval from DBx to CBx in tertiles was 0-8.8, 8.9-12.4 and > 12.5 months. For simplicity, rates of reclassification on CBx were calculated at 13 months post-DBx. Multivariable logistic regression determined association between reclassification, CBx timing, and other clinical and pathologic parameters. RESULTS: 90 men (21.3%) experienced reclassification on CBx. CBx was performed 11 months (median) after DBx (IQR 7.8-13.8). Rates of reclassification at 13 months were 23.5% (28/ 199 CBx), 19.5% (34/174 CBx), and 21.7% (28/129 CBx), respectively (p1⁄40.71). On multivariable analysis factors associated with reclassification were BMI and prostate volume. BMI (categorized as 35 kg/m (OR 6.1 95% CI 2.0, 18.7) compared to those with BMI < 30 kg/m. Moderate (30-60ml; OR 0.28 95% CI 0.14, 0.57) and large (60mlþ; OR 0.14 95% CI 0.05, 0.40) prostate volume were associated with decreased odds of reclassification compared to volume

Aim: We aimed to develop a comprehensive Colorectal cancer Risk Prediction Tool (CRiPT). To achieve this, it is necessary to incorporate germline mutations in the DNA mismatch repair genes and MUTYH to account for a proportion of the familial aggregation of colorectal cancer. Population prevalence of these mutations and the genetic and environmental causes of the remaining familial aggregation, however, are not known. Methods: We studied the families of 5,744 colorectal cancer cases (probands) recruited from population cancer registries in the USA, Canada and Australia, and screened probands for mutations in the mismatch repair genes MLH1, MSH2, MSH6, and PMS2, and MUTYH. We fitted modified segregation analysis models to the cancer history of first-degree relatives, conditional on the age at diagnosis of the proband, using the software MENDEL. We determined the genetic model that best explained the familial aggregation of colorectal cancer by estimating the prevalence of mutations in the known susceptibility genes, the prevalence of and hazard ratio for unmeasured high-risk gene mutations, and the variance of the unmeasured polygenic component, using a χ2 goodness-of-fit test. Results: The best fitting model was a mixed dominant model with the polygenic standard deviation varying by age. Under that model, we estimated 1 in 279 of the population carry mutations in the mismatch repair genes (MLH = 1 in 1946, MSH2 = 1 in 2841, MSH6 = 1 in 758, PMS2 = 1 in 714), 1 in 45 carry mutations in MUTYH, and 1 in 504 carry mutations in unknown major gene(s) which are associated with on average a 31-fold increased risk of colorectal cancer. The estimated variance of the polygenic component decreased from 1.8 for age Conclusion: CRiPT is a comprehensive prediction model that incorporates both known and unknown major genes and polygenes. CRiPT can provide the probabilities of having a mutation in a DNA mismatch repair gene or MUTYH as well as estimate future risk (e.g., 5-year risk) of developing colorectal cancer. This model is similar to the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) that calculates for women the probabilities of carrying a BRCA1 or BRCA2 mutation and their future risk of developing breast and ovarian cancer based on their family history. Further work will include measured environmental factors and genetic variants to CRiPT, and it will be useful for genetic counselling and targeted colorectal cancer screening in clinical practices. This abstract is also being presented as Poster B04. Citation Format: Aung Ko Win, Mark A. Jenkins, James G. Dowty, Antonis C. Antoniou, Andrew Lee, Yingye Zheng, Noralane M. Lindor, Polly A. Newcomb, John L. Hopper, Robert J. MacInnis. Development of a comprehensive colorectal cancer risk prediction tool (CRiPT) incorporating known and unknown major genes and polygenes. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr PR10.