Citations

Objective To examine the use of the Prostate Health Index ( PHI ) as a continuous variable in multivariable risk assessment for aggressive prostate cancer in a large multicentre US study. Materials and Methods The study population included 728 men, with prostate‐specific antigen ( PSA ) levels of 2–10 ng/ mL and a negative digital rectal examination, enrolled in a prospective, multi‐site early detection trial. The primary endpoint was aggressive prostate cancer, defined as biopsy Gleason score ≥7. First, we evaluated whether the addition of PHI improves the performance of currently available risk calculators (the Prostate Cancer Prevention Trial [ PCPT ] and European Randomised Study of Screening for Prostate Cancer [ ERSPC ] risk calculators). We also designed and internally validated a new PHI ‐based multivariable predictive model, and created a nomogram. Results Of 728 men undergoing biopsy, 118 (16.2%) had aggressive prostate cancer. The PHI predicted the risk of aggressive prostate cancer across the spectrum of values. Adding PHI significantly improved the predictive accuracy of the PCPT and ERSPC risk calculators for aggressive disease. A new model was created using age, previous biopsy, prostate volume, PSA and PHI , with an area under the curve of 0.746. The bootstrap‐corrected model showed good calibration with observed risk for aggressive prostate cancer and had net benefit on decision‐curve analysis. Conclusion Using PHI as part of multivariable risk assessment leads to a significant improvement in the detection of aggressive prostate cancer, potentially reducing harms from unnecessary prostate biopsy and overdiagnosis.

AimsThe International Collaboration on Cancer Reporting (ICCR) is a not‐for‐profit organization formed by the Royal Colleges of Pathologists of Australasia and the United Kingdom, the College of American Pathologists, the Canadian Association of Pathologists–Association Canadienne des Pathologists in association with the Canadian Partnership Against Cancer, and the European Society of Pathology. Its goal is to produce standardized, internationally agreed, evidence‐based datasets for use throughout the world.Methods and resultsThis article describes the development of a cancer dataset by the multidisciplinary ICCR expert panel for the reporting of thymic epithelial tumours. The dataset includes ‘required’ (mandatory) and ‘recommended’ (non‐mandatory) elements, which are validated by a review of current evidence and supported by explanatory text. Seven required elements and 12 recommended elements were agreed by the international dataset authoring committee to represent the essential information for the reporting of thymic epithelial tumours.ConclusionsThe use of an internationally agreed, structured pathology dataset for reporting thymic tumours provides all of the necessary information for optimal patient management, facilitates consistent and accurate data collection, and provides valuable data for research and international benchmarking. The dataset also provides a valuable resource for those countries and institutions that are not in a position to develop their own datasets.

Purpose To determine the effects of carfilzomib, lenalidomide, and dexamethasone (KRd) versus lenalidomide and dexamethasone (Rd) on health-related quality of life (HR-QoL) in the Carfilzomib, Lenalidomide, and Dexamethasone Versus Lenalidomide and Dexamethasone for the Treatment of Patients With Relapsed Multiple Myeloma (ASPIRE) trial. Methods Patients with relapsed multiple myeloma were randomly assigned to receive KRd or Rd. The European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire C30 and myeloma-specific module were administered at baseline; day 1 of cycles 3, 6, 12, and 18; and after treatment. The Global Health Status/Quality of Life (GHS/QoL) scale and seven subscales (fatigue, nausea and vomiting, pain, physical functioning, role functioning, disease symptoms, and adverse effects of treatment) were compared between groups using a mixed model for repeated measures. The percentages of responders with ≥ 5- or 15-point GHS/QoL improvement at each cycle were compared between groups. Results Baseline questionnaire compliance was excellent (94.1% of randomly assigned patients). KRd patients had higher GHS/QoL scores versus Rd patients over 18 treatment cycles (two-sided P < .001). The minimal important difference was met at cycle 12 (5.6 points) and approached at cycle 18 (4.8 points). There was no difference between groups for the other prespecified subscales from ASPIRE. A higher proportion of KRd patients met the GHS/QoL responder definition (≥ 5-point improvement) with statistical differences at cycle 12 (KRd v Rd patients, 25.5% v 17.4%, respectively) and 18 (KRd v Rd patients, 24.2% v 12.9%, respectively). Conclusion KRd improves GHS/QoL without negatively affecting patient-reported symptoms when compared with Rd. These data further support the benefit of KRd in patients with relapsed multiple myeloma.

Background The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study. Methods We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T>G and c.3113G>A, CHEK2 c.349A>G, c.538C>T, c.715G>A, c.1036C>T, c.1312G>T, and c.1343T>G and ATM c.7271T>G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant. Results For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10−5), PALB2 c.3113G>A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10−8) and ATM c.7271T>G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A>G OR 2.26 (95% CI 1.29 to 3.95), c.1036C>T OR 5.06 (95% CI 1.09 to 23.5) and c.538C>T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T>G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G>T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants. Conclusions This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.

Abstract Background: The strongest known risk factor for endometrial cancer is obesity. To determine whether SNPs associated with increased body mass index (BMI) or waist–hip ratio (WHR) are associated with endometrial cancer risk, independent of measured BMI, we investigated relationships between 77 BMI and 47 WHR SNPs and endometrial cancer in 6,609 cases and 37,926 country-matched controls. Methods: Logistic regression analysis and fixed effects meta-analysis were used to test for associations between endometrial cancer risk and (i) individual BMI or WHR SNPs, (ii) a combined weighted genetic risk score (wGRS) for BMI or WHR. Causality of BMI for endometrial cancer was assessed using Mendelian randomization, with BMIwGRS as instrumental variable. Results: The BMIwGRS was significantly associated with endometrial cancer risk (P = 3.4 × 10−17). Scaling the effect of the BMIwGRS on endometrial cancer risk by its effect on BMI, the endometrial cancer OR per 5 kg/m2 of genetically predicted BMI was 2.06 [95% confidence interval (CI), 1.89–2.21], larger than the observed effect of BMI on endometrial cancer risk (OR = 1.55; 95% CI, 1.44–1.68, per 5 kg/m2). The association attenuated but remained significant after adjusting for BMI (OR = 1.22; 95% CI, 1.10–1.39; P = 5.3 × 10−4). There was evidence of directional pleiotropy (P = 1.5 × 10−4). BMI SNP rs2075650 was associated with endometrial cancer at study-wide significance (P &lt; 4.0 × 10−4), independent of BMI. Endometrial cancer was not significantly associated with individual WHR SNPs or the WHRwGRS. Conclusions: BMI, but not WHR, is causally associated with endometrial cancer risk, with evidence that some BMI-associated SNPs alter endometrial cancer risk via mechanisms other than measurable BMI. Impact: The causal association between BMI SNPs and endometrial cancer has possible implications for endometrial cancer risk modeling. Cancer Epidemiol Biomarkers Prev; 25(11); 1503–10. ©2016 AACR.