JNCI Cancer Spectrum最新文献

Chemotherapy-induced nausea and vomiting are among the most distressing side effects of cancer therapy. Younger age is a risk factor for chemotherapy-induced nausea and vomiting, and cancer incidence is rising among young adults ages 18-39 years. However, the comparative burden of chemotherapy-induced nausea and vomiting in young adults vs non-young adults remains insufficiently understood. This study compared acute and delayed chemotherapy-induced nausea and vomiting between young adults and non-young adults (ie, ages 40 years and older) after the first infusion of moderately or highly emetogenic chemotherapy. Of 1609 participants, 159 (10%) were young adults. Rates of guideline-consistent antiemetic prophylactic care were similar between groups (65% young adults, 71% non-young adults; P = .11). Despite this, acute nausea was more prevalent (69% vs 40%; P < .001) and severe (mean [SD] = 3.9 [2.6] vs mean = 3.0 [2.3] on 0-10 scale; P < .001) among young adults vs non-young adults. Similarly, delayed nausea was more prevalent (85% vs 69%; P < .001) and severe (mean = 4.5 [2.4] vs mean = 3.7 [2.5]; P < .001) among young adults. Findings may inform clinical approaches to managing chemotherapy-induced nausea and vomiting among young adults.

Background: Prostate cancer disproportionately affects vulnerable populations. The All of Us Research Program (AoURP) is a database that aims to encapsulate the diversity of the United States. To explore the utility of this dataset in assessing prostate cancer disparities, we investigated whether treatment usage, disease progression, and genomic research participation vary across sociodemographic factors among AoURP participants with prostate cancer.

Methods: We identified AoURP participants with prostate cancer. Genomic research participation in AoURP, treatment usage, time-to-treatment, and time-to-metastasis were assessed by demographics and distance from a National Cancer Institute-designated comprehensive cancer center. Multivariable logistic regression and Cox proportional hazards regression were performed to evaluate treatment usage and time-to-treatment and time-to-metastasis, respectively.

Results: We observed lower genomic data availability in Black vs White patients (P < .001). In multivariable analyses, patients residing more than 80 miles from an NCI-designated comprehensive cancer center were less likely to receive androgen receptor pathway inhibitors (odds ratio [OR] = 0.30, 95% CI = 0.14 to 0.66; P = .002) and bone targeting agents (OR = 0.46, 95% CI = 0.30 to 0.70; P < .001) but more likely to undergo prostatectomy (OR = 1.97, 95% CI = 1.43 to 2.71; P < .001) than those residing less than 40 miles away. These patients also initiated treatment faster (hazard ratio [HR] = 1.54, 95% CI = 1.27 to 1.87; P < .001) and developed metastasis slower (HR = 0.58, 95% CI = 0.40 to 0.86; P = .006). Black patients were less likely to receive radiation (OR = 0.45, 95% CI = 0.23 to 0.88; P = .020), prostatectomy (OR = 0.65, 95% CI = 0.44 to 0.96; P = .028), and bone targeting agents (OR = 0.65, 95% CI = 0.45 to 0.93; P = .018) than White patients.

Conclusions: Prostate cancer treatment usage, disease progression, and genomic research participation varied between demographic populations. As AoURP matures, additional studies may leverage future data releases to confirm these findings.

Background: Colorectal cancer (CRC) outcomes vary by both race and ethnicity, and screening test use may contribute to this variation. We examined the association of race, ethnicity, and associated factors with CRC screening test use in a setting where financial barriers to screening are mitigated.

Methods: Survey information was gathered from US Veteran participants (N = 50,125) when enrolled into a randomized trial comparing screening colonoscopy to annual fecal immunochemical testing (FIT) in the prevention of CRC mortality. The primary exposures of interest were the participants' self-identified race and ethnicity, with adjustment for variables capturing access to care. Multivariable logistic regression, stratified by site and age, was used to assess the relationship between exposures of interest and prior use of any CRC screening test, prior colonoscopy, and prior fecal occult blood test (FOBT, including FIT) use.

Results: Screening test use was common (N = 28,330, 56.5%) with more Veterans reporting prior FOBT (N = 20,386, 40.7%) than prior colonoscopy (N = 12,671, 25.3%). In multivariable analysis, Black participants were more likely (odds ratio (OR), 1.06; 95% confidence interval (CI) 1.01-1.12) to have had any prior screening relative to White persons and this finding was driven by more frequent FOBT use relative to White persons (OR, 1.16; 95% CI 1.10-1.23). There was no association between Hispanic ethnicity (relative to White persons) on the primary outcomes.

Conclusions: In this cohort, prior screening test use was common, with observed variation in overall test use by race, but not ethnicity. Further study of CRC screening test use in diverse populations are needed.

Clinicaltrials.gov id: NCT#05612347.

Purpose: Cancer-related cognitive impairment is common in patients receiving cancer treatment but may be under detected by clinician-graded adverse events (AEs) alone. Patient-reported outcomes and cognitive screening may improve identification of cognitive symptoms.

Methods: We conducted a secondary analysis of the nationwide, multicenter GAP70+ trial of adults aged ≥70 years with advanced cancer starting systemic therapy. Cognitive symptoms were assessed longitudinally using patient-reported and clinician-graded cognitive AEs, and Mini-Cog screening at baseline, 4-6 weeks, 3 months, and 6 months. We examined prevalence, longitudinal trajectories, and associations with Mini-Cog impairment. Statistical significance was set at two-sided p< 0.05.

Results: Among 704 participants (mean age, 77.2 years; range, 70 to 96 years), patient-reported cognitive AEs were more prevalent than clinician-graded cognitive AEs at all timepoints: 19% vs 0.48% at 4 to 6 weeks, 18% vs 2.5% at 3 months, and 22% vs 0.44% at 6 months at 6 months (all p < 0.001). Patient-reported cognitive AEs also fluctuated within patients over time. Impaired Mini-Cog was associated with higher patient-reported cognitive AEs at all post-baseline timepoints: 31% vs 15% at 4 to 6 weeks, 34% vs 14% at 3 months, and 49% vs 15%at 6 months (all p < 0.001). In contrast, associations with clinician-graded cognitive AEs were observed only at 3 months (p = 0.004) and 6 months (p = 0.04).

Conclusions: Cognitive symptomatic AEs are common and often under detected by clinician grading alone in older adults with advanced cancer. Combining patient-reported AEs with brief cognitive screening may improve detection during treatment.

Purpose: To evaluate the impact of a virtual oncology financial and legal navigation (OFLN) intervention on cancer-related financial toxicity (FT) and health-related quality of life (QOL) in pediatric and adolescent and young adult (PAYA) cancer patients and caregivers, as well as assess the intervention's acceptability and feasibility.

Methods: A single-arm trial was conducted in a PAYA oncology clinic between March 2024 and May 2025. Pre- and post-intervention surveys included the Comprehensive Score for Financial Toxicity (COST), Patient-Reported Outcomes Measurement Information System global health, anxiety and depression scales, National Comprehensive Cancer Network's Distress Thermometer, and intervention acceptability, appropriateness and feasibility of Measures.

Results: The majority (36 patients and 88 caregivers) identified as female (73%), non-Hispanic White (85%), rural residents (61%), with incomes above the federal poverty level (71%). Participants reported moderate levels of FT at baseline with mean COST of 20.9 (SD = 11.14) for patients and 19.3 (SD = 10.12) for caregivers and high levels of anxiety, depression, and distress. Among caregivers, there was a significant (p = 0.01) post-intervention increase in COST (indicating decreased FT). Almost all patients reported decreases in subjective stress and anxiety (94%) and feeling better prepared to navigate financial/legal issues. Participants rated the intervention highly across implementation outcomes of acceptability (76%), appropriateness (76%), and feasibility (75%), which was also supported by 89% enrollment and 95% retention rates.

Conclusion: Findings demonstrate that virtual OFLN has the potential to increase access to supportive care services especially in rural communities. Additional research supporting scalability and uptake for widespread implementation is needed.

Background: Neighborhood gentrification leads to displacement of people, networks, and resources, and to differences in how income is distributed in the community. Few studies, however, have examined the roles of neighborhood gentrification and income inequality in relation to cancer incidence, particularly among Hispanic/Latino populations. We examined measures of neighborhood gentrification and income distribution in association with cancer risk among Hispanic/Latino adults.

Methods: We included 14,303 adults (ages 18-75 years) from the Hispanic Community Health Study/Study of Latinos with geocoded addresses at baseline in 2008-2011. Incident cancers diagnosed from baseline through 2021 were ascertained via linkages with four state cancer registries. Neighborhood gentrification from 2000-2010 was assessed using the Gentrification Index. Income inequality in 2005-2009 was assessed using the Gini Coefficient. Multivariable survey-weighted Cox regression estimated hazard ratios (HR) and 95% confidence intervals (CI) for the associations between quartiles of gentrification and income inequality and cancer incidence. We also conducted stratified analyses by household-level poverty (FPL), HCHS/SOL field center, and insurance status.

Results: A total of 701 incident cancers were diagnosed over a mean follow-up of 10.4 (range=0.1-13.8) years. Those in Gentrification Index Quartile 4 (vs. Q1) had a 43% increase in cancer risk (HR = 1.43; 95%CI=1.02-2.01), and those in Gini coefficient Quartile 4 (vs. Q1) had a 52% increase in cancer risk (HR = 1.52; 95%CI=1.03-2.26). Associations varied by health insurance status, but not by FPL or field center.

Conclusion: The highest versus lowest levels of neighborhood gentrification and income inequality were associated with increases in cancer risk among Hispanic/Latino adults.

Background: Hepatocellular carcinoma(HCC) is the sixth most common cancer and the third leading cause of cancer-related death worldwide. Our updated network meta-analysis aims to compare and rank first-line treatment regimens for advanced HCC.

Methods: We searched PubMed, EMBASE, Scopus, and Cochrane from inception to May 2025 for phase III RCTs investigating first-line systemic therapies for advanced HCC. Derived hazard ratios(HRs) for each study were pooled in a random-effects NMA. The primary outcome was overall survival(OS), progression-free survival(PFS), objective response rate(ORR), and ≥ Grade 3 treatment-related adverse events(TRAE) of the assessed treatment in comparison to Sorafenib and Lenvatinib. Subgroup analysis for OS and PFS was conducted using study-level HRs. P-scores were used to rank the treatment strategies numerically.

Results: Seventeen studies involving 12,727 patients were included in the final analysis. Nivolumab-Ipilimumab(HR:0.61,95%CI:0.44-0.84), Atezolizumab-Bevacizumab(HR:0.66,95%CI:0.48-0.90), Durvalumab-Tremelimuma(HR:0.76,95%CI:0.59-0.97), Sintilimab-BevSim(HR:0.57,95%CI:0.41-0.80), and Camrelizumab-Rivoceranib(HR:0.62,95%CI:0.45-0.85) had superior OS compared to Sorafenib. Only Sintilimab-BevSim(HR:0.66,95%CI:0.44-0.99) and Nivolumab-Ipilimumab(HR:0.70,95%CI:0.54-0.92) had superior OS compared to Lenvatinib. Based on p-score rankings only, Nivolumab-Ipilimumab had the highest p-score for OS, PFS, and ORR among the three FDA and EMA approved combination regimens, with similar ≥ Grade 3 TRAE compared to Sorafenib. In the subgroup analysis, Atezolizumab-Cabozantinib has the highest p-score for HBV, Atezolizumab-Bevacizumab the highest for HCV, Durvalumab-Tremelimumab for non-viral aetiology, and Pembrolizumab-Lenvatinib for AFP≥400.

Conclusion: Our NMA comprehensively compares therapeutic regimens across key clinical outcomes, including OS, PFS, ORR, and ≥ Grade 3 TRAE. The heterogeneity in treatment responses across patient subgroups underscores the importance of personalized approaches in managing HCC.

Artificial intelligence (AI) is increasingly being integrated into oncology for applications including cancer detection, risk stratification, treatment planning, and clinical documentation. Concerningly, growing evidence demonstrates that AI systems can reproduce or amplify existing disparities across patient populations. Although considerable effort has focused on developing computational methods to reduce algorithmic bias, many challenges surrounding fairness extend beyond technical implementation. In this commentary, we examine algorithmic fairness in oncology from both technical and normative perspectives. We review common sources of bias throughout the machine learning pipeline, discuss major statistical definitions of fairness, including demographic parity, calibration, and equalized odds, and highlight the inherent trade-offs among these metrics. We further explore how fairness often conflicts with overall predictive performance, arguing that model selection inevitably reflects ethical judgments rather than purely technical optimization. We discuss the limitations of current bias mitigation strategies and contend that many disparities rooted in historical and structural inequities cannot be resolved through algorithmic interventions alone. Finally, we outline priorities for the responsible development and deployment of clinical AI, including greater transparency in fairness decisions, context-specific evaluation standards, ongoing post-deployment auditing, and stronger regulatory oversight. Achieving equitable AI in oncology will require coordinated efforts among developers, clinicians, regulators, and patients to ensure that these technologies improve outcomes without perpetuating existing inequities.

Few studies have compared oncologic outcomes directly between English-speaking (ES) and non-English-speaking (NES) patients. We performed a matched cohort study of Stage I-III breast cancer patients with ES patients propensity matched 3:1 to NES patients based on age, tumor stage, nodal involvement, and receipt of adjuvant therapy. Patients were categorized as ES or NES based on preferred language documented in the electronic medical record. Primary outcomes were locoregional recurrence (LRR), disease-free survival (DFS), and overall survival (OS). Among 2768 patients (2076 ES; 692 NES), median age at diagnosis was 62 years (range, 25-94). 10-year LRR was 9.5% versus 13% (P = 0.032), 10-year DFS was 71% versus 63% (P = 0.008), and 10-year OS was 79% versus 74% (P = 0.12) for ES and NES patients, respectively. These findings suggest NES patients may have inferior breast cancer outcomes, even in highly resourced academic environments. These findings highlight the need for targeted interventions beyond language assistance.

Introduction: Curative-intent treatment for pancreatic ductal adenocarcinoma (PDAC) necessitates major surgery and chemotherapy, yet many patients do not undergo resection. Frailty may contribute to this phenomenon, but its prevalence and association with pancreatectomy in PDAC remains poorly defined. This study describes the distribution of frailty and its association with curative-intent surgery in a nationally representative cohort of patients with non-metastatic PDAC.

Methods: Using SEER-Medicare data (2013-2019), we identified patients ≥66-years-old with non-metastatic PDAC. Frailty was categorized as non-frail, pre-frail, mildly frail, or moderately-to-severely frail using the Claims-based Frailty Index over the 12 months preceding diagnosis. We evaluated frailty distributions via kernel density estimation. We assessed the association between frailty category and receipt of surgery via logistic regression.

Results: Among 8,237 patients (mean age 78, 57.6% female, 77.4% White), 2,486 underwent curative-intent pancreatectomy (30.2%). Surgery was performed in 39.7% of non-frail and 30.7% of pre-frail patients; after adjustment, pre-frail patients had similar odds of resection compared to non-frail patients [aOR = 1.01, 95% CI = (0.89-1.16)]. In contrast, 15.8% of mildly frail and 5.7% of moderately-to-severely frail patients underwent surgery; both groups had significantly lower odds of surgery versus non-frail patients [mildly frail aOR = 0.53, 95% CI = (0.43-0.66); moderately-to-severely frail aOR = 0.18, 95% CI = (0.11-0.30)].

Conclusions: Remarkably, less than 40% of non-frail patients with non-metastatic PDAC underwent surgery, suggesting that curative-intent treatment remains infrequent even amongst lower-risk adults. Frailty is also common and strongly associated with decreased odds of surgical resection.