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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. [ABSTRACT FROM AUTHOR]

Nested case control (NCC) is a sampling method widely used for developing and evaluating risk models with expensive biomarkers on large prospective cohort studies. In a typical NCC design, biomarker values are obtained on a subcohort, where cases consist of all the events (subjects who experience the event during the follow‐up). However, when the number of events is not small, due to the cost and limited availability of biospecimen, one may select only a subset of events as cases. We refer to such a variation as the untypical NCC. Unfortunately, existing inverse probability weighted (IPW) estimators for the untypical NCC are biased, and they only focus on relative risk parameters under the proportional hazards (PH) model. In this manuscript, we propose new weighting methods that produce consistent IPW estimators for not only relative risk parameters but also several metrics that evaluate a risk model's predictive performance. We also provide the inference procedure via perturbation resampling, which captures all the variance and between‐subject covariance induced by the sampling processes for both case and control selections. In addition, our methods are not limited to the PH model, and they can be applied to the time‐specific generalized linear model. Under the typical NCC design, our new weights are equivalent to the weight proposed by Samuelsen; under the untypical NCC, the IPW estimators using our weights have smaller bias and variance than the existing methods. We will demonstrate this improved performance via both analytical and numerical investigations. [ABSTRACT FROM AUTHOR]

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. Some men on active surveillance for prostate cancer will eventually choose to be treated even in the absence of clinical progression of their disease. These decisions may be driven in part by quality‐of‐life concerns or the involvement of spouses. [ABSTRACT FROM AUTHOR]

Summary: The nested case‐control (NCC) design has been widely adopted as a cost‐effective sampling design for biomarker research. Under the NCC design, markers are only measured for the NCC subcohort consisting of all cases and a fraction of the controls selected randomly from the matched risk sets of the cases. Robust methods for evaluating prediction performance of risk models have been derived under the inverse probability weighting framework. The probabilities of samples being included in the NCC cohort can be calculated based on the study design ''a previous study'' or estimated non‐parametrically ''a previous study''. Neither strategy works well due to model mis‐specification and the curse of dimensionality in practical settings where the sampling does not entirely follow the study design or depends on many factors. In this paper, we propose an alternative strategy to estimate the sampling probabilities based on a varying coefficient model, which attains a balance between robustness and the curse of dimensionality. The complex correlation structure induced by repeated finite risk set sampling makes the standard resampling procedure for variance estimation fail. We propose a perturbation resampling procedure that provides valid interval estimation for the proposed estimators. Simulation studies show that the proposed method performs well in finite samples. We apply the proposed method to the Nurses' Health Study II to develop and evaluate prediction models using clinical biomarkers for cardiovascular risk. [ABSTRACT FROM AUTHOR]

Dynamic treatment regimes are sequential decision rules that adapt throughout disease progression according to a patient's evolving characteristics. In many clinical applications, it is desirable that the format of the decision rules remains consistent over time. Unlike the estimation of dynamic treatment regimes in regular settings, where decision rules are formed without shared parameters, the derivation of the shared decision rules requires estimating shared parameters indexing the decision rules across different decision points. Estimation of such rules becomes more complicated when the clinical outcome of interest is a survival time subject to censoring. To address these challenges, we propose two novel methods: censored shared-Q-learning and censored shared-O-learning. Both methods incorporate clinical preferences into a qualitative rule, where the parameters indexing the decision rules are shared across different decision points and estimated simultaneously. We use simulation studies to demonstrate the superior performance of the proposed methods. The methods are further applied to the Framingham Heart Study to derive treatment rules for cardiovascular disease. [ABSTRACT FROM AUTHOR]

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 < .05). In addition, suggestive associations were noted for tagging SNPs in cystathionine-β-synthase (CBS), dihydrofolate reductase (DHFR), DNA (cytosine-5-)-methyltransferase 3β (DNMT3B), methionine adenosyltransferase I α (MAT1A), MTHFD1, and MTRR (nominal P < .05; adjusted P, not significant). Significant interactions between nutrient biomarkers and candidate polymorphisms were observed for 1) plasma/RBC folate and folate hydrolase 1 (FOLH1), paraoxonase 1 (PON1), transcobalamin II (TCN2), DNMT1, and DNMT3B; 2) plasma PLP and TYMS TS3; 3) plasma B12 and betaine-homocysteine S-methyltransferase 2 (BHMT2); and 4) homocysteine and methylenetetrahydrofolate reductase (MTHFR) and alanyl-transfer RNA synthetase (AARS).Conclusions: Genetic variants in FOCM genes are associated with CRC risk among postmenopausal women. FOCM nutrients continue to emerge as effect modifiers of genetic influences on CRC risk. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 <200 IU/day was associated with a lower risk of non-small cell lung cancer among former smokers [HR = 0.36, 95% confidence interval (CI) = 0.13-0.96]. Total vitamin D intake ≥400 versus <400 IU/day was associated with a lower risk of total lung cancer among participants who received the CARET active intervention (HR = 0.56, 95% CI = 0.32-0.99) and among those who had total vitamin A intake ≥1,500 µg/day retinol activity equivalent (RAE; HR = 0.46, 95% CI = 0.23-0.91). The beneficial associations were attenuated among those who did not receive the CARET active intervention or who had total vitamin A intake <1,500 µg/day RAE ( p-interaction = 0.02 for current smokers). Our observation suggests that vitamin A may assist vitamin D in preventing lung cancer among smokers. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract: Many tissue kallikrein (KLK) genes and proteins are candidate diagnostic, prognostic and predictive biomarkers for ovarian cancer (OCa). We previously demonstrated that the KLK locus (19q13.3/4) is subject to copy-number gains and structural rearrangements in a pilot study of cell lines and ovarian cancer primary tissues, shown to overexpress KLK gene family members. To determine the overall frequency of genomic instability and copy-number changes, a retrospective study was conducted using formalin-fixed paraffin embedded (FFPE) tissues. Eighty-one chemotherapy naïve serous OCas were examined using 3-colour fluorescence in situ hybridization (FISH) to identify structural and numerical changes on 19q, including the KLK locus; in addition to immunohistochemistry (IHC) for KLK6, which has been shown to be overexpressed in OCa. The KLK locus was subject to copy-number changes in ∼83% of cases: net gain in 51%, net loss in 30% and amplified in 2%; and found to be chromosomally unstable (p < 0.001). All cases showed a wide range of immuoreactivity for KLK6 by IHC. Although no strong correlation could be found with copy-number, the latter was contributing factor to the observed KLK6 protein overexpression. Moreover, univariate and multivariate analyses showed an association between the net loss of the KLK locus and longer disease-free survival. Interestingly, FISH analyses indicated that chromosome 19q was subjected to structural rearrangement in 62% of cases and was significantly correlated to tumor grade (p < 0.001). We conclude that numerical and structural aberrations of chromosome 19q, affect genes including the KLK gene members, may contribute to ovarian carcinoma progression and aggressiveness. [ABSTRACT FROM AUTHOR]