Background: There is a male predominance of acute myeloid leukemia (AML) incidence, but survival data are conflicting. The objective of this study is to carry out a comprehensive analysis of sex differences in AML, and to investigate the impact of sex disparities in survival.Methods: The cohort included patients ≥18 years diagnosed with AML (2010–2022). Demographics, treatment patterns, treatment adverse events, and survival were analyzed. The population was described and compared by sex, and sex‐based risks and associations were obtained via Cox proportional‐hazards regression.Results: In total, 1020 AML patients were analyzed (57.4% males), with lower risk of death for females (aHR = 0.41, 95% CI 0.26–0.66). Among females, BMT (aHR = 0.51, 95% CI 0.27–0.97), hospitalization record (aHR = 0.65, 95%CI 0.45–0.93), and higher appointment completion rates (aHR = 0.98, 95% CI 0.98–0.98) were associated with lower risk of death. Overall, and similarly in males, higher age at diagnosis (aHR = 1.03, 95% CI 1.02–1.04) and a TP53 mutation (aHR = 2.24, 95% CI 1.69–2.97) were associated with higher risk of death.Conclusion: Sex differences exist in both AML incidence and overall survival. Treatment and health care factors should be addressed by caregivers and public policies developed to reduce mortality rates and mitigate existing sex differences.

Multiparametric MRI provides prognostic information, and pairing information from MRI with molecular characterization from biopsy samples may assist prostate cancer risk stratification. Background Although prostate MRI is routinely used for the detection and staging of localized prostate cancer, imaging-based assessment and targeted molecular sampling for risk stratification are a...

Cardiovascular disease is the leading cause of mortality among breast cancer (BC) patients aged 50 and above. Machine Learning (ML) models are increasingly utilized as prediction tools, and recent evidence suggests that incorporating social determinants of health (SDOH) data can enhance its performance. This study included females ≥ 18 years diagnosed with BC at any stage. The outcomes were the diagnosis and time-to-event of major adverse cardiovascular events (MACEs) within two years following a cancer diagnosis. Covariates encompassed demographics, risk factors, individual and neighborhood-level SDOH, tumor characteristics, and BC treatment. Race-specific and race-agnostic Extreme Gradient Boosting ML models with and without SDOH data were developed and compared based on their C-index. Among 4309 patients, 11.4% experienced a 2-year MACE. The race-agnostic models exhibited a C-index of 0.78 (95% CI 0.76–0.79) and 0.81 (95% CI 0.80–0.82) without and with SDOH data, respectively. In non-Hispanic Black women (NHB; n = 765), models without and with SDOH data achieved a C-index of 0.74 (95% CI 0.72–0.76) and 0.75 (95% CI 0.73–0.78), respectively. Among non-Hispanic White women (n = 3321), models without and with SDOH data yielded a C-index of 0.79 (95% CI 0.77–0.80) and 0.79 (95% CI 0.77–0.80), respectively. In summary, including SDOH data improves the predictive performance of ML models in forecasting 2-year MACE among BC females, particularly within NHB.

To evaluate the association of the Genomic Prostate Score (GPS) assay result with biochemical recurrence (BCR), distant metastases (DM), and prostate-specific death (PCD) in unfavorable intermediate (UFI) risk prostate cancer patients. The GPS assay is used to help guide management decisions for newly diagnosed low and favorable intermediate (FI) risk disease. GPS results from 2 studies (Center for Prostate Disease Research [CPDR]; Kaiser Permanente Northern California [KPNC]) in men treated with radical prostatectomy were analyzed to determine associations of the GPS result with BCR, DM, and PCD in UFI risk disease. Analyses included 299 intermediate risk prostate patients, 175 of whom had UFI risk disease (KPNC=103; CPDR=72). The GPS result as a dichotomous value (≤40 vs >40) was a significant predictor of BCR in UFI patients in multivariate analyses (hazard ratio [HR] 6.0; 95% confidence interval [CI] 2.0-22.4; P=.0035) (CPDR). GPS was a strong predictor of all 3 endpoints in multivariate analyses (BCR HR 7.1; 95% CI 5.7-8.8; P<.0001; DM HR 5.4; 95% CI 3.8-7.8; P<.0001; PCD HR 3.4; 95% CI 1.5-8.9; P=.006) (KPNC). UFI patients with GPS >40 had outcomes consistent with high-risk disease, whereas UFI patients with GPS ≤40 had outcomes similar to FI risk patients (CPDR/KPNC). The GPS result was a strong independent predictor of BCR, DM, and PCD in intermediate risk prostate cancer. UFI patients with GPS >40 have a poor prognosis and may benefit from additional therapeutic options.

Although ~40% of screen-detected prostate cancers (PCa) are indolent, advanced-stage PCa is a lethal disease with 5-year survival rates around 29%. Identification of biomarkers for early detection of aggressive disease is a key challenge. Starting with 52 candidate biomarkers, selected from existing PCa genomics datasets and known PCa driver genes, we used targeted mass spectrometry to quantify proteins that significantly differed in primary tumors from PCa patients treated with radical prostatectomy (RP) across three study outcomes: (i) metastasis ≥1-year post-RP, (ii) biochemical recurrence ≥1-year post-RP, and (iii) no progression after ≥10 years post-RP. Sixteen proteins that differed significantly in an initial set of 105 samples were evaluated in the entire cohort (n = 338). A five-protein classifier which combined FOLH1, KLK3, TGFB1, SPARC, and CAMKK2 with existing clinical and pathological standard of care variables demonstrated significant improvement in predicting distant metastasis, achieving an area under the receiver-operating characteristic curve of 0.92 (0.86, 0.99, p = 0.001) and a negative predictive value of 92% in the training/testing analysis. This classifier has the potential to stratify patients based on risk of aggressive, metastatic PCa that will require early intervention compared to low risk patients who could be managed through active surveillance.

Background: Premature aging has been identified as a global risk factor for cancer. Causes of premature aging are multifactorial, including inflammation, infection, chronic stress, and lifestyle factors.Method: We evaluated whether premature aging in people living with HIV (PLWH) was associated with antiretroviral therapy (ART) or the diagnosis of cancer. We used well‐established DNA methylation patterns to assess premature aging, using Horvath et al., in individuals with HIV located in Cleveland, Ohio and compared these to standardized datasets of US historical blood samples. Some of the PLWH developed cancer over time.Results: We found that DNA methylation analysis identified accelerated aging in PLWH whereas ART therapy mitigated the advancement of DNA methylation age. A variety of cancers were observed in this population, but a cancer diagnosis was not significantly associated with more advanced DNA methylation age.Conclusion: We find that the age acceleration detected in PLWH is mitigated by ART therapy and is not further accelerated by a diagnosis of cancer.