JNCI Cancer Spectrum最新文献

High upfront cost may be a barrier to adopting chimeric antigen receptor T-cell (CAR-T) therapy for relapsed or refractory B-cell lymphoma. Data on the real-world costs are limited. Using the Blue Cross Blue Shield Axis database, we evaluated 271 commercially insured patients who received CAR-T therapy for B-cell lymphoma (median age = 58 years; men = 68%; diffuse large B-cell lymphoma = 87%; inpatient CAR-T therapy = 85%). Our peri-CAR-T period of interest was from 41 days before to 154 days after CAR-T therapy index divided into seven 28-day intervals. Median total costs were $608 100 (interquartile range, IQR = $534 100-$732 800); 8.5% of patients had total costs exceeding $1 million. The median cost of CAR-T therapy products was $402 500, and the median out-of-pocket copayment was $510. Monthly costs were highest during the month of CAR-T therapy administration (median = $521 500), with median costs below $25 000 in all other 28-day intervals. Costs of CAR-T therapy use were substantial, largely driven by product acquisition. Future studies should examine the relationship between costs, access, and financial outcomes.

Innovative strategies to increase clinical trial accessibility and equity are needed. We conducted a retrospective review of a phase II investigator-initiated trial to determine whether the modification of clinical trial design to decentralize study treatment can improve trial accessibility among underrepresented groups. Sociodemographic characteristics, including area deprivation indices, as well as study site travel distance, time, and costs were compared between enrolled participants who received chemotherapy locally and participants who did not. Participants who received chemotherapy locally lived substantially farther from the study site (median = 95.90 vs 25.20 miles, P = .004), faced a greater time burden traveling to the study site (median = 115.00 vs 34.00 minutes, P = .002), and had higher travel-related costs for a single trip to the study site (median = $62.81 vs $16.51, P = .004). This study highlights opportunities for alleviating financial and time burdens associated with clinical trial participation, promoting equity in clinical research. Trial Registration: ClinicalTrials.gov identifier: NCT04380337.

Background: There are few studies of social support and other social determinants of health after breast cancer diagnosis and their associations with mortality; results have been inconclusive. Further, it is not known if observed associations are specific to women with breast cancer diagnosis or if associations would be similar among healthy women.

Methods: Women with incident, pathologically confirmed invasive breast cancer, stage I-IV (n = 1012), and healthy frequency age-matched participants (n = 2036) answered a social support questionnaire in prospective follow-up of a population-based case-control study, the Western New York Exposures and Breast Cancer Study. At interview, all participants were aged 35-79 years and resident of 2 counties in Western New York State. Mortality status was ascertained from the National Death Index. Participants were queried regarding the number of their close friends, frequency of seeing them, household size, household income, and marital status. Hazard ratios (HRs) and 95% confidence intervals (CIs) for breast cancer-specific mortality (breast cancer women only) and all-cause mortality were estimated.

Results: Lower household income was associated with higher all-cause mortality among women diagnosed with breast cancer (HR = 2.48, 95% CI = 1.24 to 4.97) and similarly among the healthy women (HR = 2.63, 95% CI = 1.25 to 5.53). Number and frequency of seeing friends, marital status, and household size were not associated with mortality, either among breast cancer patients or among healthy women.

Conclusion: Among those diagnosed with breast cancer and healthy women, lower income was associated with more than twice the mortality. Marital status, household size, and number or frequency of meeting friends were not associated with survival.

Background: Neighborhood socioeconomic deprivation has been linked to adverse health outcomes, yet it is unclear whether neighborhood-level social determinants of health (SDOH) measures affect overall survival in adolescent and young adult patients with cancer.

Methods: This study used a diverse cohort of adolescent and young adult patients with cancer (N = 10 261) seen at MD Anderson Cancer Center. Zip codes were linked to Area Deprivation Index (ADI) values, a validated neighborhood-level SDOH measure, with higher ADI values representing worse SDOH.

Results: ADI was statistically significantly worse (P < .050) for Black (61.7) and Hispanic (65.3) patients than for White patients (51.2). Analysis of ADI by cancer type showed statistically significant differences, mainly driven by worse ADI in patients with cervical cancer (62.3) than with other cancers. In multivariable models including sex, age at diagnosis, cancer diagnosis, and race and ethnicity, risk of shorter survival for people residing in neighborhoods with the least favorable ADI quartile was greater than for individuals in the most favorable ADI quartile (hazard ratio = 1.09, 95% confidence interval = 1.00 to 1.19, P = .043).

Conclusion: Adolescent and young adult patients with cancer and the worst ADI values experienced a nearly 10% increase in risk of dying than patients with more favorable ADI values. This effect was strongest among White adolescent and young adult survivors. Although the magnitude of the effect of ADI on survival was moderate, the presence of a relationship between neighborhood-level SDOH and survival among patients who received care at a tertiary cancer center suggests that ADI is a meaningful predictor of survival. These findings provide intriguing evidence for potential interventions aimed at supporting adolescent and young adult patients with cancer from disadvantaged neighborhoods.

Background: Receipt of chimeric antigen receptor T-cell (CAR-T) therapy at an institution different from the primary oncologist's institution is a complex, multistep process. Referral by oncologists plays an important role in the process but may be susceptible to bias.

Methods: Oncologists who previously referred patients for CAR-T therapy at 5 pediatric hospitals were sent surveys by email exploring their CAR-T referral practices. Descriptive statistics were generated, and multivariate analyses examined associations among oncologist characteristics, familiarity with CAR-T therapy, and referral practices. We conducted semistructured interviews with a subset of participants and used thematic analysis to code transcripts.

Results: Sixty-eight oncologists completed the survey; 77% expressed being "very familiar" with CAR-T therapy. Hispanic oncologists and oncologists at institutions with 50 or fewer new diagnoses per year were more likely to identify as less familiar with CAR-T therapy (odds ratio [OR] = 64.3, 95% confidence interval [CI] = 2.45 to 10 452.50, P = .04 and OR = 24.5, 95% CI = 3.3 to 317.3, P = .005, respectively). In total, 38% of respondents considered nonclinical features (compliance, social support, resources, insurance, language, education, and race or ethnicity) influential in referral decisions. Oncologists who were Hispanic and oncologists who had been practicing for 20 or more years were more likely to consider these features significantly influential (OR = 14.52, 95% CI = 1.49 to 358.66, P = .04 and OR = 6.76, 95% CI = 1.18 to 50.5, P = .04). Nine oncologists completed in-depth interviews; common themes included barriers and concerns regarding CAR-T therapy referral, the value of an established relationship with a CAR-T therapy center, and poor communication after CAR-T therapy.

Conclusions: Nearly 40% of oncologists consider nonclinical features significantly influential when deciding to refer patients for CAR-T therapy, raising concern for bias in the referral process. Establishing formal partnerships with CAR-T therapy centers may help address physician barriers in referral.

Background: Prior studies demonstrate that 20%-50% of adolescents and young adults (age 15-39 years) with acute lymphoblastic leukemia (ALL) receive care at specialty cancer centers, yet a survival benefit has been observed for patients at these sites. Our objective was to identify patients at risk of severe geographic barriers to specialty cancer center-level care.

Methods: We used data from the North American Association of Central Cancer Registries Cancer in North America database to identify adolescent and young adult ALL patients diagnosed between 2004 and 2016 across 43 US states. We calculated driving distance and travel time from counties where participants lived to the closest specialty cancer center sites. We then used multivariable logistic regression models to examine the relationship between sociodemographic characteristics of counties where adolescent and young adult ALL patients resided and the need to travel more than 1 hour to obtain care at a specialty cancer center.

Results: Among 11 813 adolescent and young adult ALL patients, 43.4% were aged 25-39 years, 65.5% were male, 32.9% were Hispanic, and 28.7% had public insurance. We found 23.6% of adolescent and young adult ALL patients from 60.8% of included US counties would be required to travel more than 1 hour one way to access a specialty cancer center. Multivariable models demonstrate that patients living in counties that are nonmetropolitan, with lower levels of educational attainment, with higher income inequality, with lower internet access, located in primary care physician shortage areas, and with fewer hospitals providing chemotherapy services are more likely to travel more than 1 hour to access a specialty cancer center.

Conclusions: Substantial travel-related barriers exist to accessing care at specialty cancer centers across the United States, particularly for patients living in areas with greater concentrations of historically marginalized communities.

CHEK2 is considered to be involved in homologous recombination repair (HRR). Individuals who have germline pathogenic variants (gPVs) in CHEK2 are at increased risk to develop breast cancer and likely other primary cancers. PARP inhibitors (PARPi) have been shown to be effective in the treatment of cancers that present with HRR deficiency-for example, caused by inactivation of BRCA1/2. However, clinical trials have shown little to no efficacy of PARPi in patients with CHEK2 gPVs. Here, we show that both breast and non-breast cancers from individuals who have biallelic gPVs in CHEK2 (germline CHEK2 deficiency) do not present with molecular profiles that fit with HRR deficiency. This finding provides a likely explanation why PARPi therapy is not successful in the treatment of CHEK2-deficient cancers.

Background: We aimed to define levels of unmet supportive care needs in people with primary brain tumor and to reach expert consensus on feasibility of addressing patients' needs in clinical practice.

Methods: We conducted secondary analysis of a prospective cohort study of people diagnosed with high-grade glioma (n = 116) who completed the Supportive Care Needs Survey-Short Form during adjuvant chemoradiation therapy. Participants were allocated to 1 of 3 categories: no need ("no need" for help on all items), low need ("low need" for help on at least 1 item, but no "moderate" or "high" need), or moderate/high need (at least 1 "moderate" or "high" need indicated). Clinical capacity to respond to the proportion of patients needing to be prioritized was assessed.

Results: Overall, 13% (n = 5) were categorized as no need, 23% (n = 27) low need, and 64% (n = 74) moderate/high need. At least 1 moderate/high need was reported in the physical and daily living domain (42%) and the psychological (34%) domain. In recognition of health system capacity, the moderate/high need category was modified to distinguish between moderate need ("moderate" need indicated for at least 1 item but "high" need was not selected for any item) and high need (at least 1 "high" need indicated). Results revealed 24% (n = 28) moderate need and 40% (n = 46) high need. Those categorized as high need indicated needing assistance navigating the health system and information.

Conclusions: Using four step allocations resulted in 40% of patients indicating high need. Categories may facilitate appropriate triaging and guide stepped models of healthcare delivery.

Deep learning-based mammographic evaluations could noninvasively assess response to breast cancer chemoprevention. We evaluated change in a convolutional neural network-based breast cancer risk model applied to mammograms among women enrolled in SWOG S0812, which randomly assigned 208 premenopausal high-risk women to receive oral vitamin D3 20 000 IU weekly or placebo for 12 months. We applied the convolutional neural network model to mammograms collected at baseline (n = 109), 12 months (n = 97), and 24 months (n = 67) and compared changes in convolutional neural network-based risk score between treatment groups. Change in convolutional neural network-based risk score was not statistically significantly different between vitamin D and placebo groups at 12 months (0.005 vs 0.002, P = .875) or at 24 months (0.020 vs 0.001, P = .563). The findings are consistent with the primary analysis of S0812, which did not demonstrate statistically significant changes in mammographic density with vitamin D supplementation compared with placebo. There is an ongoing need to evaluate biomarkers of response to novel breast cancer chemopreventive agents.