JNCI Cancer Spectrum最新文献

{"title":"Predictors of LexisNexis residential history availability and registry data concordance for childhood cancer research.","authors":"Natalie R Binczewski, Libby M Morimoto, Joseph L Wiemels, Xiaomei Ma, Catherine Metayer, Veronica M Vieira","doi":"10.1093/jncics/pkaf075","DOIUrl":"https://doi.org/10.1093/jncics/pkaf075","url":null,"abstract":"<p><strong>Background: </strong>Use of a commercial database to obtain residential history information in environmental epidemiologic studies of cancer can lead to information bias if data availability varies by individual socio-demographic factors or case status. Residential data that is not missing at random and data that is discordant with cancer registry or birth record address data can impact subsequent exposure assessments. In our study of childhood cancers, we aimed to determine if availability of residential history information differs by case status or other potential confounders and if there was agreement with cancer registry and birth records address data.</p><p><strong>Methods: </strong>We worked with LexisNexis to retrieve residential histories for mothers of 3,573 childhood cancer cases and 7,160 controls born 2000-2015 in Los Angeles and Orange Counties in Southern California. We used linear regression to determine independent predictors of having residential history returned by LexisNexis. We assessed concordance between maternal address at birth and child's address at diagnosis available from registry data and the LexisNexis residential history by comparing street addresses and geocoded coordinates.</p><p><strong>Results: </strong>Maternal characteristics (birthplace, race and ethnicity, education, insurance provider) and child's case status were associated with the mother having any address returned by LexisNexis. When comparing geocoded coordinates of cases, < 10% of LexisNexis addresses during the diagnosis year matched cancer registry addresses. Birth record addresses matched LexisNexis-provided addresses for 47% of mothers.</p><p><strong>Conclusions: </strong>This study elucidates potential implications of using commercial databases such as LexisNexis to reconstruct residential histories and derive exposure measures in cancer case-control studies.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144717917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of postoperative FDG-PET/CT on adjuvant head and neck cancer treatment.","authors":"P Travis Courtney, Jesus E Juarez Casillas, Eulanca Y Liu, Myung-Shin Sim, Lydia W Chau, Rafael E Lopez-Chicas, Maie A St John, Elliot Abemayor, Keith E Blackwell, Dinesh K Chhetri, Quinton S Gopen, Paul A Kedeshian, Rhorie P Kerr, Jivianne K Lee, Vishad Nabili, Joel A Sercarz, Jeffrey D Suh, Marilene B Wang, Deborah J Wong, Wanxing Chai-Ho, Mahbod G Jafarvand, Shadfar Bahri, Erika Jank, Vishruth K Reddy, Michael L Steinberg, Robert K Chin, Ricky R Savjani","doi":"10.1093/jncics/pkaf077","DOIUrl":"https://doi.org/10.1093/jncics/pkaf077","url":null,"abstract":"<p><strong>Background: </strong>Residual or recurrent cancer after surgery but prior to adjuvant therapy occurs in a proportion of patients with head and neck cancer and may warrant treatment changes. 18-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) may help identify residual or recurrent disease but is not routinely obtained. We evaluated the relevance of postoperative FDG-PET/CT in this clinical context.</p><p><strong>Methods: </strong>This single-institution, retrospective study identified patients with head and neck cancer who underwent definitive surgery between January 1, 2013, and April 1, 2023, and received a postoperative FDG-PET/CT prior to adjuvant treatment. We measured the rates of management changes resulting from postoperative FDG-PET/CT findings and the association between having a postoperative FDG-PET/CT which resulted in a management change and oncologic outcomes with selected multivariable competing-risks and proportional hazards regressions.</p><p><strong>Results: </strong>Of 150 patients, sixty-six (44.0%) had a management change because of the postoperative FDG-PET/CT findings. Sixty-two (93.8%) had radiotherapy plan changes, 20 (30.3%) underwent additional diagnostic testing, 11 (16.7%) had systemic therapy added or changed, 3 (4.6%) underwent reresection, and 15 (10.0%) switched to palliative-intent treatment. Having a postoperative FDG-PET/CT which resulted in a management change was not significantly associated with cancer recurrence or overall survival (both p > .05).</p><p><strong>Conclusion(s): </strong>In patients with resected head and neck cancer, postoperative, pre-adjuvant therapy FDG-PET/CT can alter clinical management and may enable additional personalization of treatment. When practical to obtain without delaying treatment, postoperative FDG-PET/CT may have clinical utility though requires careful interpretation due to the risks of false positives.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144698570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extending catchment area approaches to a community cancer center: a breast cancer hotspot case-study.","authors":"Scott D Siegel, Yuchen Zhang, Ross Budziszewski, Atif Bacchus, Jennifer Rowland, Mary V Iacocca, Robert Hall-Mcbride, Frank C Curriero","doi":"10.1093/jncics/pkaf067","DOIUrl":"https://doi.org/10.1093/jncics/pkaf067","url":null,"abstract":"<p><strong>Background: </strong>The National Cancer Institute (NCI) requires that NCI-Designated Cancer Centers develop programs to reduce the burden of cancer within their catchment areas, or the geographic area they serve. Extending catchment area approaches to community cancer centers has the potential to meaningfully reduce the burden of cancer nationwide. Building on a prior report that identified two advanced breast cancer (BC) hotspots (geographic areas with significantly elevated rates of BC) in a community cancer center catchment area, the objective of this study was to identify screening-related and tumor biology factors that explain the advanced BC hotspots.</p><p><strong>Methods: </strong>Logistic regressions were used to model the relationship between BC screening interval and odds of advanced BC in a catchment area-based cohort of 3,492 breast cancer patients, adjusting for demographic and tumor characteristics. The observed to expected case ratios were used to evaluate how well the regression models explained the hotspots.</p><p><strong>Results: </strong>In models adjusted for grade, molecular subtype, and histology, patients with inconsistent BC screening had more than twice the odds of advanced breast cancer as patients who screened regularly. The model largely explained one of the hotspots and approximately half of the excess cases observed for the second hotspot.</p><p><strong>Conclusions: </strong>In a community cancer center catchment area, BC screening and tumor biology were associated with increased odds of advanced BC and helped to explain previously detected hotspots. Specific community outreach and engagement interventions are considered for these hotspots while broader implications for extending catchment area approaches to community cancer centers are discussed.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144682633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FDA pooled analysis of OS according to depth of response in frontline advanced IO RCC trials.","authors":"Elaine Chang, Haley Gittleman, Chi Song, Erik Bloomquist, Laura Fernandes, Chana Weinstock, Sundeep Agrawal, Nicole Gormley, Shenghui Tang, Daniel L Suzman, Laleh Amiri-Kordestani, Richard Pazdur, Paul G Kluetz, David F McDermott, Meredith M Regan, Brian I Rini","doi":"10.1093/jncics/pkaf069","DOIUrl":"https://doi.org/10.1093/jncics/pkaf069","url":null,"abstract":"<p><strong>Background: </strong>Retrospective analyses of studies of immune-oncology (IO)-containing combinations for advanced renal cell carcinoma (aRCC) suggest that depth of response (DepOR) is associated with overall survival (OS), but have methodologic limitations. We investigated the relationship of Week 12 DepOR as a continuous variable with OS.</p><p><strong>Methods: </strong>Pooling data from patients with treatment (tx)-naïve aRCC enrolled in randomized IO-containing frontline aRCC trials submitted to FDA that included Week 12 imaging assessment, we developed 36-month (mo) OS prediction models based on Week 12 DepOR (reduction from baseline in target lesion diameters) using Cox proportional hazards with natural spline in IO combination and sunitinib (SUN) groups. To avoid guarantee-time bias, only patients in follow-up at Week 12 scan were included. OS was defined from Week 12 imaging date.</p><p><strong>Results: </strong>Among the 4 trials meeting inclusion criteria, 1364 patients in IO combination and 1267 patients in SUN group had Week 12 imaging.DepOR and 36-month OS were correlated throughout the entire range of DepOR in both tx groups, with no plateau in OS as DepOR approached complete response. Across the range of DepOR, estimated 36-mo OS was higher in IO combination group.</p><p><strong>Conclusion: </strong>Deeper response was associated with better 36-month OS in this pooled exploratory analysis of tx-naive aRCC patients treated with IO combination or SUN.Further work characterizing the relationship between DepOR and OS at the trial level may advance understanding of the utility of DepOR as a pharmacodynamic response biomarker or early endpoint in signal-seeking trials and to facilitate efficient drug development.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144649470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unplanned hospitalization among advanced prostate cancer patients by diabetes status-a population-based study.","authors":"Amy L Shaver, Krupa Gandhi, Scott W Keith, Nikita Nikita, Christopher C Yang, Felix J Kim, Hushan Yang, William Kevin Kelly, Stephen J Freedland, Grace Lu-Yao","doi":"10.1093/jncics/pkaf070","DOIUrl":"https://doi.org/10.1093/jncics/pkaf070","url":null,"abstract":"<p><strong>Background: </strong>Older adults with advanced prostate cancer (PCa) and type 2 diabetes mellitus (T2DM) are under-represented in trials of androgen receptor pathway inhibitors (ARPIs). This study examined changes in unplanned hospitalization rates in patients receiving ARPIs by T2DM status and assessed if unplanned hospitalization varies according to ARPI.</p><p><strong>Methods: </strong>This population-based study of PCa patients over age 66 utilized SEER-Medicare data. Pre-post ARPI initiation changes and ARPI differences in unplanned hospitalization rates were estimated by adjusted incidence rate ratios (aIRR) with considerations for interactions between period, ARPI, and T2DM status. Linear contrasts were used to estimate and test conditional aIRRs. Tests were two-sided and p < .05 was considered statistically significant.</p><p><strong>Results: </strong>The study included 12,240 patients: 3,160 with T2DM (25.8%), 7,191 (58.8%) received AAP and 5,049 (41.2%) ENZA. Unplanned hospitalization rates increased after ARPI initiation by 65% among patients with T2DM complications (aIRR 1.65; 95% CI 1.37, 1.98) and 109% in non-diabetics (aIRR 2.09; 95% CI 1.94, 2.26). Among patients with T2DM without complications, the increase in unplanned hospitalization rates depended on the ARPI initiated: 103% after AAP (aIRR 2.03; 95% CI 1.70, 2.43) and 47% after ENZA (aIRR 1.47; 95% CI 1.21, 1.80), a 38% greater increase in unplanned hospitalization rates after AAP than ENZA (ratio of aIRRAAP/aIRRENZA 1.38; 95% CI 1.06, 1.80).</p><p><strong>Conclusions: </strong>All patients had higher unplanned hospitalization rates after ARPI. Our findings highlight the importance of using real-world data to better understand the interplay between pre-existing health conditions and treatment outcomes, a critical step toward precision medicine.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144649471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"INTEGRATE pooled phase 2/3 results are robust to postprogression switching and the winner's curse.","authors":"Yu Yang Soon, Katrin Sjoquist, Ian C Marschner, I Manjula Schou, Nick Pavlakis, David Goldstein, Kohei Shitara, Martin R Stockler, John Simes, Andrew J Martin","doi":"10.1093/jncics/pkaf053","DOIUrl":"10.1093/jncics/pkaf053","url":null,"abstract":"<p><strong>Background: </strong>The INTEGRATE phase 3 trial in advanced gastric and esophagogastric junction cancer involved pooling overall survival data with its preceding phase 2 trial, raising concerns about misalignment due to treatment switching in phase 2, or the \"winner's curse.\" We evaluated phase 2 results, adjusted for these opposing effects, against phase 3 according to the prespecified statistical analysis plan.</p><p><strong>Methods: </strong>Overall survival estimates were adjusted for treatment switching using the rank-preserving structural failure time model (RPSFTM) and inverse probability of censoring weights (IPCW) method. A novel shrinkage approach mitigated overestimation from the winner's curse, and Bayesian prediction methods predicted phase 3 outcomes from phase 2 estimates. A simulation study modeled 10 000 seamless phase 2/3 trials to quantify bias in the pooled estimate.</p><p><strong>Results: </strong>The observed phase 3 hazard ratio (HR = 0.71, 95% CI = 0.54 to 0.93) for overall survival was more conservative than the adjusted phase 2 estimates (RPSFTM and novel shrinkage approach: HR = 0.61, 95% CI = 0.29 to 1.29; RPSFTM and Bayesian prediction: HR = 0.59, 95% CI = 0.48 to 0.73; IPCW and novel shrinkage approach: HR = 0.55, 95% CI = 0.31 to 0.99; IPCW and Bayesian prediction: HR = 0.58, 95% CI = 0.46 to 0.72). Simulations indicated negligible bias in the pooled log hazard ratio of ‒0.011 and 0.005 under the null and alternative hypotheses, respectively.</p><p><strong>Conclusion: </strong>Adjusting phase 2 estimates for both treatment switching and the winner's curse produced point estimates similar to the unadjusted phase 3 results. A prospective plan to pool trial data under a closed testing procedure may be a reasonable strategy when a recruitment shortfall in phase 3 is anticipated, provided that potential sources of misalignment are thoroughly assessed.</p><p><strong>Clinical trial information: </strong>ACTRN12612000239864 (INTEGRATE I)NCT02773524 (INTEGRATE IIA).</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12212049/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144199063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Disparities in tissue-based biomarker testing among US Medicare beneficiaries with prostate cancer.","authors":"Stephan M Korn, Zhiyu Qian, Hanna Zurl, Andrea Piccolini, Klara K Pohl, Stuart Lipsitz, Jianyi Zhang, Adam S Kibel, Caroline M Moore, Huma Q Rana, Kerry L Kilbridge, Shahrokh F Shariat, Stacy Loeb, Quoc-Dien Trinh, Alexander P Cole","doi":"10.1093/jncics/pkaf051","DOIUrl":"10.1093/jncics/pkaf051","url":null,"abstract":"<p><strong>Background: </strong>Personalized therapeutic approaches for localized prostate cancer have evolved significantly, with tissue-based biomarker tests supplementing traditional risk stratification tools. However, national testing patterns and geographic variability remain limited a decade after coverage implementation. We aimed to assess current nationwide utilization and urban-rural differences in tissue-based biomarker testing.</p><p><strong>Methods: </strong>Using full Medicare claims data, we retrospectively identified patients with newly diagnosed prostate cancer and tissue-based biomarker testing claims from 2019 to 2023. Patients' county of residence was categorized as metro, urban, or rural. Regional testing rates were further assessed across hospital referral regions. A multivariable logistic regression model was performed to assess the effect of residence on test receipt.</p><p><strong>Results: </strong>Our final cohort included 749 202 patients, of whom 79.5% lived in metro, 11.4% in urban and 8.00% in rural counties. Overall, 86 908 (11.6%) patients underwent tissue-based biomarker tests. Hospital referral region-level testing rates ranged from 2.4% to 42.7%. Rural patients were 18% less likely to undergo testing compared to metro patients (odds ratio [OR] 0.82, 95% CI = 0.73 to 0.91). Independently, the odds of undergoing testing were lower among Black (OR 0.82, 95% CI = 0.77 to 0.88) and Hispanic patients (OR 0.80, 95% CI = 0.73 to 0.88) compared to White patients.</p><p><strong>Conclusion: </strong>This study reveals high geographic variability in tissue-based biomarker testing for prostate cancer. Further, Black and Hispanic patients were less likely to receive testing. Our findings highlight regional practice variation in the use of advanced, not routinely recommended tests and underscore the need to minimize disparities in diagnostic access.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12212051/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144078142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Socioeconomic disparities and bladder cancer stage at diagnosis: a statewide cohort analysis.","authors":"Alessio Finocchiaro, Anna Tylecki, Silvia Viganò, Alessandro Bertini, Vincenzo Ficarra, Ettore Di Trapani, Andrea Salonia, Alberto Briganti, Francesco Montorsi, Giovanni Lughezzani, Nicolò Buffi, Akshay Sood, Craig Rogers, Firas Abdollah","doi":"10.1093/jncics/pkaf054","DOIUrl":"10.1093/jncics/pkaf054","url":null,"abstract":"<p><strong>Background: </strong>Bladder cancer is the ninth most common cancer worldwide. Despite its prevalence, large-scale studies on the relationship between socioeconomic disparities and disease stage at presentation are lacking. This study examines the association between the Area Deprivation Index (ADI), a robust measure of socioeconomic status, and stage at diagnosis among bladder cancer patients.</p><p><strong>Methods: </strong>Patients diagnosed with bladder cancer (any TNM stage) from the Michigan Department of Health and Human Services (2004-2019) were retrospectively analyzed. ADI was assigned based on patients' residential census-block group and stratified into quartiles, with the fourth quartile (ADI 75-100) representing the most deprived. Multivariable logistic regression tested the impact of ADI on advanced disease stages (muscle invasive disease [≥T2], positive nodal status [cN+], metastatic disease [cM+]).</p><p><strong>Results: </strong>Among 29 010 patients, the majority were non-Hispanic White (92%), males (75%), and residents in metropolitan areas (81%). Patients in the third and fourth ADI quartiles had higher rates of ≥T2 (22%, 24.5%) compared with the first and second quartiles (18%, 19.5%) (P < .001), as well as increased rates of cN+ (3.4%, 3.7%) and cM+ (2.8%, 3.2%) (P < .001). Multivariable regression showed that each 10-unit rise in ADI increased odds of T2 by 4% (95% CI = 1.03 to 1.06, P < .001), cN+ by 4% (95% CI = 1.01 to 1.07, P = .038), and cM+ by 6% (95% CI = 1.02 to 1.09, P = .003).</p><p><strong>Conclusion: </strong>Higher ADI correlates with advanced bladder cancer stages at diagnosis. Addressing these disparities is essential to improve outcomes in bladder cancer care.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12274062/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144187002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk of early death after acute leukemia diagnosis among adolescents and young adults.","authors":"Amy M Berkman, Clark R Andersen, Vidya Puthenpura, Nicholas J Short, Kelly Merriman, Mahesh Swaminathan, Branko Cuglievan, David McCall, Courtney DiNardo, Cesar Nunez, Nitin Jain, Tapan Kadia, Ghayas Issa, Amber Gibson, Miriam B Garcia, J Andrew Livingston, Susan Parsons, Michelle A T Hildebrandt, Michael E Roth","doi":"10.1093/jncics/pkaf065","DOIUrl":"10.1093/jncics/pkaf065","url":null,"abstract":"<p><strong>Background: </strong>Advances in care have led to improvements in survival for adolescents and young adults (AYAs) diagnosed with cancer; however, the risk of early death remains high for certain cancers, particularly acute leukemias. Risk factors for early death in AYAs diagnosed with acute leukemia have not been well studied.</p><p><strong>Methods: </strong>The Surveillance, Epidemiology, and End Results registry was used to assess risk of early death (within 2 months of diagnosis) in AYAs diagnosed with acute leukemia (n = 16 153). Early death proportion, by year, for AYAs diagnosed between 2006 and 2020 was described. Associations between incidence of early death and age at diagnosis, sex, race and ethnicity, socioeconomic status, rurality, acute leukemia type, and year of diagnosis were evaluated with logistic regression.</p><p><strong>Results: </strong>Overall, 6.0% of AYAs experienced early death and there was a significant annual decrease in the odds of early death (odds ratio [OR] = 0.96, 95% confidence interval [CI] = 0.95 to 0.98, P < .0001) across the study period. Over the entire study period, AYAs diagnosed with acute promyelocytic leukemia (9.6%, 95% CI = 8.4 to 11.1) or other acute leukemias (13.3%, 95% CI = 10.5 to 16.7) had the highest proportion of early death and AYAs diagnosed with T lymphoblastic leukemia/lymphoma had the lowest (2.6%, 95% CI = 1.9 to 3.7). Older age at diagnosis, male sex, and Hispanic ethnicity were all associated with increased risk of early death.</p><p><strong>Conclusions: </strong>A high proportion of AYAs with acute leukemia experience early death and risk varies by leukemia type and sociodemographic factors. A better understanding of the complex interplay between disease biology and sociodemographic factors is needed to guide risk prediction and prevention.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12231595/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144511951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Meat consumption and risk of hepatobiliary cancers in the National Institutes of Health-AARP Diet and Health Study.","authors":"David Wahl, Erikka Loftfield, Sémi Zouiouich, Linda M Liao, Hyokyoung G Hong, Katherine A McGlynn, Rashmi Sinha","doi":"10.1093/jncics/pkaf068","DOIUrl":"10.1093/jncics/pkaf068","url":null,"abstract":"<p><strong>Background: </strong>We investigated the relationship between intakes of red, white, and processed meats with liver cancer-including hepatocellular carcinoma and intrahepatic cholangiocarcinoma, gallbladder cancer, and other biliary tract cancers.</p><p><strong>Methods: </strong>The analytic cohort consisted of 480 347 US adults in the prospective National Institutes of Health-AARP Diet and Health Study who were cancer-free at baseline at ages 50-71 years. With a median follow-up of 19.68 years, we identified 1150 participants with incident liver cancer (219 intrahepatic cholangiocarcinomas and 931 hepatocellular carcinomas), 231 with incident gallbladder cancer, and 472 with other incident biliary tract cancers (272 extrahepatic cholangiocarcinomas). At baseline, a self-administered food frequency questionnaire assessed usual dietary intake. We used multivariable Cox proportional hazards models to estimate the associations of meat type with hepatobiliary cancers. We used substitution models with the \"leave-one-out\" approach as our primary analysis and addition models as a supplemental analysis.</p><p><strong>Results: </strong>Replacing red meat with white meat was inversely associated with liver cancer (hazard ratio [HR]50 g/1000 kcal = 0.62, 95% CI = 0.51 to 0.77), hepatocellular carcinoma (HR50 g/1000 kcal = 0.63, 95% CI = 0.50 to 0.80), and intrahepatic cholangiocarcinoma (HR50 g/1000 kcal = 0.56, 95% CI = 0.35 to 0.90). Because of the symmetry of substitution models, replacing white meat with red meat yielded hazard ratios equal to the reciprocal of these values, indicating increased risk for the same cancer sites. No associations were observed for meat intake and gallbladder or other biliary tract cancers.</p><p><strong>Conclusions: </strong>Our study indicates replacing intake of red meat with white meat could lower risk of liver cancer by nearly 40%, whereas replacing white meat with red meat could increase the risk by more than 60%.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":4.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144583888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}