Citations

Abstract The incidence of venous thromboembolism (VTE) in patients with acute lymphoblastic leukemia (ALL) receiving asparaginase-based induction is high despite primary thromboprophylaxis. Our aim was to derive and externally validate a VTE risk prediction model in patients with ALL receiving asparaginase-based induction. We conducted a multicenter retrospective cohort study of patients (aged ≥18 years) with newly diagnosed ALL receiving asparaginase-based induction. The derivation and external validation cohorts included 306 and 94 patients, respectively. Primary outcome was VTE at any site. A cause-specific Cox proportional hazards model stratified by thromboprophylaxis and center was performed to identify VTE risk factors in the derivation cohort. A risk prediction model for VTE at 30 days was derived using variables with P value < .05 in the multivariable model and was tested in the validation cohort. VTE risk factors on multivariable analysis in the derivation cohort included D-dimer ≥1 μg fibrinogen equivalent unit per mL (hazard ratio [HR], 2.64; 95% confidence interval [CI], 1.07-6.5) and hemoglobin (HR for each 1 g/dL increment, 1.19; 95% CI, 1.06-1.34) at ALL diagnosis. A VTE risk score based on these variables distinguished between a 4% (95% CI, 0.72-12) and 20% (95% CI, 14-27) 30-day cumulative incidence of VTE in the derivation cohort, with similar findings in the validation cohort (area under the curve, 0.56). The negative predictive value for VTE at 30 days was 96% and 93% in the derivation and validation cohorts, respectively, and the positive predictive value was 20% in both. We derived and validated a model using D-dimer and hemoglobin, which stratifies VTE risk in patients with ALL receiving asparaginase-based induction.

Abstract Purpose: Polatuzumab vedotin (polatuzumab) was approved for up-front treatment of diffuse large B-cell lymphoma in combination with chemoimmunotherapy (Pola-R-CHP) based on the POLARIX trial. However, when stratified by cell of origin (COO), polatuzumab seems to have greater efficacy in activated B-cell than germinal center B-cell (GCB) subtype disease. Most studies of polatuzumab used RNA expression to assess COO, whereas in routine clinical practice, the immunohistochemistry-based Hans algorithm is used. Experimental Design: To assess the impact of COO by immunohistochemistry on polatuzumab efficacy, we conducted a multicenter real-world study of adults with large B-cell lymphoma (LBCL) receiving polatuzumab from 2015 to 2024, split by receipt of polatuzumab in first-line versus relapsed/refractory settings. The primary endpoint was overall response rate (ORR) to polatuzumab-based treatment in GCB versus non-GCB relapsed/refractory LBCL. Results: Of 740 patients, 305 received polatuzumab in the first-line setting and 435 in the relapsed/refractory setting. In the relapsed/refractory cohort, the ORR in non-GCB versus GCB LBCL was 59.7% versus 36.3% [OR, 2.6; 95% confidence interval (CI), 1.77–3.84; P < 0.0001], with a complete response rate of 35.7% versus 17.7% (OR, 2.6; 95% CI, 1.66–4.02; P < 0.0001). Progression-free survival was longer for patients with non-GCB versus GCB COO (HR, 0.64; 95% CI, 0.5–0.83; P = 0.0006). In the first-line cohort, ORR, complete response rate, and progression-free survival were similar in non-GCB versus GCB LBCL, as hypothesized based on outcomes in the Pola-R-CHP arm of POLARIX, suggesting that the addition of polatuzumab overcomes the adverse risk of non-GCB COO in patients receiving R-CHOP. Conclusions: Based on these data, COO classification by the Hans algorithm is a strong predictor of polatuzumab efficacy in LBCL, informing real-world treatment decisions.

Prostate cancer (PCa) progression is driven by intricate molecular mechanisms involving dysregulated signaling networks and posttranslational modifications of key regulatory proteins. In this study, we identify a novel oncogenic pathway wherein cyclin-dependent kinase 12 (CDK12) physically interacts with and phosphorylates forkhead box A1 (FOXA1) at serine 234 (S234). Phosphorylation at this residue markedly enhances FOXA1 transcriptional activity, leading to up-regulation of downstream targets including murine double minute 2 (MDM2), a critical negative regulator of the p53 tumor suppressor. Mechanistically, this CDK12–FOXA1–MDM2 axis destabilizes p53, attenuates apoptotic signaling, and promotes PCa cell survival and proliferation. Therapeutic targeting of CDK12 using the small-molecule inhibitor THZ531 or RNA interference effectively abrogates FOXA1 phosphorylation, restores p53 stability, reactivates apoptotic pathways, and suppresses tumor growth. Notably, the identification of S234 as a functional phosphorylation site in FOXA1 reveals a previously uncharacterized posttranslational regulatory mechanism in PCa biology. These findings establish the CDK12–FOXA1–MDM2 axis as a pivotal driver of PCa progression and underscore the therapeutic potential of targeting FOXA1 phosphorylation to restore tumor suppressor function and induce apoptosis in PCa. Our work provides a mechanistic framework for developing precision therapies aimed at disrupting this oncogenic cascade in PCa.

ABSTRACT Consumer health informatics is becoming increasingly important in a world where more than 5 billion people rely on the internet and social media for health information. eHealthyinfo is a physician‐initiated and reviewed artificial intelligence (AI) applied digital health information website, aiming to be essential in advancing health literacy and promoting preventive health behaviors. To assess the effectiveness of its digital content, we conducted a mixed‐methods evaluation of 13 wellness and nutrition videos randomly selected from eHealthyinfo, representing 30% of its relevant content. Two independent reviewers used the Patient Education Materials Assessment Tool for Audiovisual Materials (PEMAT‐A/V) and the modified version of the CDC Clear Communication Index (CCI) to evaluate each video. Website log data were also analyzed to assess levels of user engagement. The average PEMAT scores were 89.5% for understandability and 100% for actionability, while the average CCI score was 94.4%, indicating the content was understandable, actionable, and clear. Weblog analysis revealed 16,000 active users, with an average engagement time of 41 seconds per user and a 27% average bounce rate for the examined year. eHealthyinfo demonstrates a strong potential as a digital health education tool, with high‐quality, user‐friendly content.

Importance Inherited pathogenic variants (PVs) in known predisposition genes can greatly increase breast cancer risk, but the combined impact of PV status, family history, and other factors on breast cancer risk in the general US population has not been well described. Objective To evaluate population-based breast cancer risk estimates for those with established PVs overall and stratified by first-degree family history of breast cancer and other factors. Design, Setting, and Participants This study used pooled data from 13 US-based breast cancer case-control studies participating in the Cancer Risk Estimates Related to Susceptibility (CARRIERS) consortium. Enrollment for individual studies occurred between 1976 and 2013, and results are based on data released March 2023, with analyses conducted from June 2022 to July 2025. Exposures PVs, breast cancer family history, self-reported race and ethnicity, and established risk factors. Main Outcomes and Measures Breast cancer rate ratios for PVs in 7 genes were estimated from the CARRIERS consortium. PV status and incidence and mortality statistics were combined using the Individualized Coherent Absolute Risk Estimation (iCARE) model to estimate conditional cumulative breast cancer risks and 95% CIs, stratified by family history and standardized to the US population. Models that incorporated population-based data and published estimates for established epidemiologic risk factors were also evaluated. Results A total of 67 692 women were studied, including 33 841 who were diagnosed with breast cancer. PVs in ATM , BRCA1 , BRCA2 , CHEK2 , and PALB2 were strongly associated with breast cancer risk, with BRCA1 and PALB2 PVs showing evidence of heterogeneity by family history. In models considering PVs, family history, and established risk factors, the estimated cumulative risks of breast cancer by age 50 years ranged from 2.4% (95% CI, 2.4-2.4) in women with no PVs and no family history to 35.5% (95% CI, 21.6-55.1) in PALB2 PV carriers with a family history. Among women who have not been diagnosed with breast cancer by age 50 years, the cumulative risk of breast cancer by age 80 years ranged from 11.1% (95% CI, 11.0-11.2) in noncarriers with no family history to 70.5% (95% CI, 52.8-83.5) for PALB2 carriers with a family history. PV-specific cumulative risk estimates varied across subgroups defined by race and ethnicity and potentially modifiable epidemiologic risk factors. Conclusions and Relevance In this study, population-based estimates of cumulative breast cancer risk for established PVs, as informed by the CARRIERS case-control sample, varied by family history and potentially modifiable risk factors. These estimates provide guidance for identifying individuals who will most benefit from enhanced screening and prevention strategies.

Abstract Frailty is highly prevalent in cardiovascular disease and associates with poor clinical outcomes. Several cardiovascular conditions benefit from invasive interventions, but the impact of these procedures in frail patients remains unclear. We thus performed a systematic review and meta-analysis to summarize evidence and quantify the pooled effect of clinical outcomes of invasive cardiovascular interventions among frail vs. non-frail patients. Systematic search of two electronic databases from January 2015 to April 2025 was performed including all randomized controlled trials (RCTs) and prospective cohort studies examining outcomes of invasive cardiovascular interventions stratified by frailty. Outcomes included all-cause mortality, hospitalizations, and other adverse outcomes. Risk ratios (RRs) and their 95% confidence intervals (CI) were assessed using random-effects models. Thirty-one studies (10 RCTs, 21 prospective, 3 retrospective studies) with a total of 27 534 participants were included. Compared with non-frail patients, frail patients after cardiovascular procedures were at higher risks of all-cause mortality (RR 3.14, 95% CI: 2.29-4.30), and hospitalizations (RR 1.88, 95% CI: 1.29-2.73). Frail patients undergoing transcatheter aortic-valve implantation and percutaneous mitral-valve interventions did not have significant increased mortality risks compared with non-frail patients (P > 0.05). Pre-frailty predicted lower mortality risks amongst patients undergoing transcatheter vs. surgical aortic valve replacement (HR 0.78, 95% CI: 0.67-0.92). Frail patients with non-ST elevation myocardial infarction derived similar mortality benefits from an invasive vs. conservative approach (HR 1.13, 95% CI: 0.64-2.01). In conclusion, frailty prognosticates adverse outcomes following invasive cardiovascular interventions and influences treatment efficacy, highlighting its significance in treatment selection

Abstract Background The isocitrate dehydrogenase (IDH) mutation status is a key molecular marker in diagnosing and treating brain tumors. Currently, it is determined via invasive tissue biopsy. Recent advances in deep learning (DL) have offered promising non-invasive alternatives for determining IDH status. However, their clinical translation is hindered by a significant gap between DL predictions and their clinical applicability. The limited transparency of many DL-networks and inadequate evaluation metrics hinders trust and adoption, as clinicians require clear and validated insights for determining IDH status. These challenges highlight the need for robust validation and measures of predictive reliability to make DL-predictions clinically actionable. Methods We developed a unique approach for non-invasive prediction of IDH status using MRI. We combine a voxel-wise-segmentation network(MC-net) with Bayesian logistic regression (BLR) to provide an IDH status and estimate confidence scores. We utilized a comprehensive dataset of 2,481 glioma cases from eight institutions. Results Our framework(MC-net + BLR) demonstrated robust performance achieving 96.4% and 95.1% classification accuracies on diverse databases, with an AUC of 0.98. The BLR was implemented exclusively on held-out test data, ensuring that the derived confidence scores are independent of the training or validation phases. The derived confidence scores showed a low Brier score of 0.0125, highlighting its superior calibration and uncertainty quantification. Conclusion The developed framework provides an IDH status and a confidence score, offering clinicians an additional layer of assurance in prediction reliability. It bridges the gap between high-performing DL models and their clinical applicability by addressing the challenges in prediction reliability. Our framework is a significant advancement in non-invasive determination of IDH-status and confidence-informed therapeutic decision-making in neuro-oncology.

We report 3-year follow-up results from TRANSFORM comparing lisocabtagene maraleucel (liso-cel) versus standard of care (SOC) for second-line primary refractory/early relapsed (≤12 months) large B-cell lymphoma (LBCL). Adults eligible for autologous stem cell transplantation (N = 184) were randomly assigned 1:1 to liso-cel (100 × 10 6 chimeric antigen receptor–positive T cells) or SOC. Results are reported descriptively. With a median follow-up of 33.9 months, median (95% CI) event-free survival was 29.5 months (9.5 to not reached [NR]) for liso-cel versus 2.4 months (2.2 to 4.9) for SOC (hazard ratio [HR], 0.375; 95% CI, 0.259 to 0.542). Median progression-free survival was NR (12.6-NR) for liso-cel versus 6.2 months (4.3-8.6) for SOC (HR, 0.422; 95% CI, 0.279 to 0.639) with 36-month rates of 51% versus 26.5%. Median overall survival (OS) was NR for both arms (HR, 0.757; 95% CI, 0.481 to 1.191), with 66% of patients crossing over to receive liso-cel; 36-month OS rate was 63% for liso-cel versus 52% for SOC. OS HR (0.566 [95% CI, 0.359 to 0.895]) favored liso-cel when accounting for the treatment effect of crossover. Safety results were consistent with previous reports. At 3-year follow-up, liso-cel confirmed superior, more durable efficacy versus SOC with a favorable safety profile and no new safety signals. These data support liso-cel as an effective second-line treatment with curative potential for relapsed/refractory LBCL.

Triple-negative breast cancer (TNBC) represents the most malignant subtype of breast cancer. The clinical application of PARP inhibitors (PARPi) is limited by the low frequency of BRCA1/2 mutations in TNBC. Here, we identified that MTAP deletion sensitized genotoxic agents in our clinical cohort of metastatic TNBC. Further study demonstrated that MTAP deficiency or inhibition rendered TNBC susceptibility to chemotherapeutic agents, particularly PARPi. Mechanistically, targeting MTAP that synergized with PARPi by disrupting the METTL16-MAT2A axis involved in methionine metabolism and depleting in vivo s-adenosylmethionine (SAM) levels. Exhausted SAM in turn impaired PARPi-induced DNA damage repair through attenuation of MRE11 recruitment and end resection by diminishing MRE11 methylation. Notably, brain metastatic TNBC markedly benefited from a lower dose of PARPi and MTAP deficiency/inhibition synergy due to the inherently limited methionine environment in the brain. Collectively, our findings revealed a feed-forward loop between methionine metabolism and DNA repair through SAM, highlighting a therapeutic strategy of PARPi combined with MTAP deficiency/inhibition for TNBC.