The Relation Between Travel Distance and Overall Survival for HPV-Associated Cancers in a High-Burden State.

Purpose: To assess the association between travel distance to an academic health system and overall survival for patients with human papillomavirus (HPV)-associated cancers. Methods: Using hospital-based cancer registry data from 2005-2019, we calculated unidirectional travel distance from each patient's geocoded address to our academic health center through network analysis. We categorized distance as short (<25 miles), intermediate (25-74.9 miles), or long (≥75 miles). The primary outcome was time from the date of initial diagnosis to the date of death or last contact. We used multivariable Cox proportional hazards regression to evaluate the association between travel distance and overall survival. We also estimated the adjusted observed 5-year survival rate. Results: Patients with HPV-associated cancers traveling distances that were intermediate (hazard ratio [HR], 1.23; 95% CI, 1.06-1.43) and long (HR, 1.15; 95% CI, 1.01-1.32) had a higher hazard of death than the short-distance group. The adjusted 5-year observed survival rates for HPV-associated cancers were lowest in the intermediate-distance group (60.4%) compared with the long-(62.6%) and short-distance (66.2%) groups. Conclusions: Our findings indicate that travel distance to an academic health center was associated with overall survival for patients with HPV-associated cancers, reflecting the importance of considering travel burden in improving patient outcomes.

Informatics tools to implement late cardiovascular risk prediction modeling for population management of high-risk childhood cancer survivors.

BACKGROUND: Clinical informatics tools to integrate data from multiple sources have the potential to catalyze population health management of childhood cancer survivors at high risk for late heart failure through the implementation of previously validated risk calculators. METHODS: The Oklahoma cohort (n = 365) harnessed data elements from Passport for Care (PFC), and the Duke cohort (n = 274) employed informatics methods to automatically extract chemotherapy exposures from electronic health record (EHR) data for survivors 18 years old and younger at diagnosis. The Childhood Cancer Survivor Study (CCSS) late cardiovascular risk calculator was implemented, and risk groups for heart failure were compared to the Children's Oncology Group (COG) and the International Guidelines Harmonization Group (IGHG) recommendations. Analysis within the Oklahoma cohort assessed disparities in guideline-adherent care. RESULTS: The Oklahoma and Duke cohorts both observed good overall concordance between the CCSS and COG risk groups for late heart failure, with weighted kappa statistics of .70 and .75, respectively. Low-risk groups showed excellent concordance (kappa > .9). Moderate and high-risk groups showed moderate concordance (kappa .44-.60). In the Oklahoma cohort, adolescents at diagnosis were significantly less likely to receive guideline-adherent echocardiogram surveillance compared with survivors younger than 13 years old at diagnosis (odds ratio [OD] 0.22; 95% confidence interval [CI]: 0.10-0.49). CONCLUSIONS: Clinical informatics tools represent a feasible approach to leverage discrete treatment-related data elements from PFC or the EHR to successfully implement previously validated late cardiovascular risk prediction models on a population health level. Concordance of CCSS, COG, and IGHG risk groups using real-world data informs current guidelines and identifies inequities in guideline-adherent care.

Rural, Large Town, and Urban Differences in Optimal Subspecialty Follow-up and Survivorship Care Plan Documentation among Childhood Cancer Survivors.

BACKGROUND: Children with cancer from rural and nonurban areas face unique challenges. Health equity for this population requires attention to geographic disparities in optimal survivorship-focused care. METHODS: The Oklahoma Childhood Cancer Survivor Cohort was based on all patients reported to the institutional cancer registry and ≤ 18 years old at diagnosis between January 1, 2005, and September 24, 2014. Suboptimal follow-up was defined as no completed oncology-related clinic visit five to 7 years after their initial diagnosis (survivors were 7-25 years old at end of the follow-up period). The primary predictor of interest was rurality. RESULTS: Ninety-four (21%) of the 449 eligible survivors received suboptimal follow-up. There were significant differences (P = 0.01) as 36% of survivors from large towns (n = 28/78) compared with 21% (n = 20/95) and 17% (n = 46/276) of survivors from small town/isolated rural and urban areas received suboptimal follow-up, respectively. Forty-five percent of adolescents at diagnosis were not seen in the clinic compared with 17% of non-adolescents (P < 0.01). An adjusted risk ratio of 2.2 (95% confidence interval, 1.5, 3.2) was observed for suboptimal follow-up among survivors from large towns, compared with survivors from urban areas. Seventy-three percent of survivors (n = 271/369) had a documented survivorship care plan with similar trends by rurality. CONCLUSIONS: Survivors from large towns and those who were adolescents at the time of diagnosis were more likely to receive suboptimal follow-up care compared with survivors from urban areas and those diagnosed younger than thirteen. IMPACT: Observed geographic disparities in survivorship care will inform interventions to promote equitable care for survivors from nonurban areas.