BackgroundRural patients experience worse cancer survival outcomes than urban patients despite similar incidence rates, due in part to significant barriers to accessing quality cancer care. Community hospitals in non-metropolitan/rural areas play a crucial role in providing care to patients who desire and are able to receive care locally. However, rural community hospitals typically face challenges to providing comprehensive care due to lack of resources. The University of Kentucky's Markey Cancer Center Affiliate Network (MCCAN) is an effective complex, multi-level intervention, improving cancer care in rural/under-resourced hospitals by supporting them in achieving American College of Surgeons Commission on Cancer (CoC) standards. With the long-term goal of adapting MCCAN for other rural contexts, we aimed to identify MCCAN's core functions (i.e., the components key to the intervention's effectiveness/implementation) using theory-driven qualitative data research methods.MethodsWe conducted eight semi-structured virtual interviews with administrators, coordinators, clinicians, and certified tumor registrars from five MCCAN affiliate hospitals that were not CoC-accredited prior to joining MCCAN. Study team members coded interview transcripts and identified themes related to how MCCAN engaged affiliate sites in improving care quality (intervention functions) and implementing CoC standards (implementation functions) and analyzed themes to identify core functions. We then mapped core functions onto existing theories of change and presented the functions to MCCAN leadership to confirm validity and completeness of the functions.ResultsIntervention core functions included: providing expertise and templates for achieving accreditation, establishing a culture of quality-improvement among affiliates, and fostering a shared goal of quality care. Implementation core functions included: fostering a sense of community and partnership, building trust between affiliates and Markey, providing information and resources to increase feasibility and acceptability of meeting CoC standards, and mentoring and empowering administrators and clinicians to champion implementation.ConclusionThe MCCAN intervention presents a more equitable strategy of extending the resources and expertise of large cancer centers to assist smaller community hospitals in achieving evidence-based standards for cancer care. Using rigorous qualitative methods, we distilled this intervention into its core functions, positioning us (and others) to adapt the MCCAN intervention to address cancer disparities in other rural contexts.

Background An association has been identified between the diagnosis-to-treatment interval (DTI) and prognostic clinical factors and outcomes in patients with previously untreated diffuse large B-cell lymphoma (DLBCL) (Maurer et al, JCO 2018). This association can result in inadvertent selection bias in clinical trials to exclude patients with aggressive disease due to the inability to delay treatment long enough to fulfill enrollment criteria, compromising the validity of clinical trial study results to the general population. A similar concern exists in the relapsed/refractory (r/r) DLBCL setting regarding patient selection bias against patients with aggressive disease requiring immediate treatment following relapse or progression. Here we examine the time from progression after immunochemotherapy (IC) to the initiation of first salvage chemotherapy and its association with outcome. Patients and Methods: Newly diagnosed patients were prospectively enrolled within 9 months of diagnosis in the University of Iowa/Mayo Clinic Lymphoma SPORE Molecular Epidemiology Resource (MER), now a subcohort of the Lymphoma Epidemiology of Outcomes (LEO) Cohort Study, and followed for progression/relapse, retreatment, and death. This analysis includes patients with their first r/r DLBCL following frontline IC who initiated aggressive salvage chemotherapy as identified and included in a previous publication (Farooq et al, BJH 2017). The progression-to-treatment interval (PTI) was defined as the time in days from date of progression from IC to initiation of salvage therapy. The date of progression was defined as either a) the date biopsy was obtained for patients who had a biopsy to confirm progressive disease or b) the date of the scan or clinical examination indicating progression in patients who did not have a biopsy performed. Event-free survival (EFS) was defined as time from initiation of first salvage therapy to progression or relapse, initiation of new anti-lymphoma therapy, or death due to any cause; overall survival (OS) was defined as time from initiation of salvage therapy until death due to any cause. Results: 162 patients with r/r DLBCL enrolled in the MER from 2002-2012 who initiated aggressive salvage chemotherapy with intent to transplant and had confirmed dates for both progression after IC and start of salvage therapy were evaluated. Median age at first progression for these patients was 64 years (range 36-76) and 104 (64%) were male. Median time from diagnosis to first progression on IC was 6.7 months (IQR: 4.6-12.7). Initial salvage therapy was R-ICE (80%), R-DHAP (8%), rituximab, oxaliplatin, cytosine arabinoside, and dexamethasone (ROAD) (6%), and other (7%). At a median follow-up of 49 months from initiation of salvage therapy (IQR: 33-74), 116 patients had died (72%). Median PTI was 6 days (IQR: 2-13). 110 patients (68%) had biopsy confirmation of disease prior to initiating salvage therapy; median PTI was 2 days (IQR: 1-7) for patients who had biopsy confirmation vs. 7 days (IQR: 3-16) in patients without biopsy confirmation, Wilcoxon p=<0.0001. There was no difference in OS from initial salvage therapy between patients who did not have biopsy confirmation (HR=1.09, 95% CI: 0.74-1.60, p=0.68) compared to patients with biopsy confirmation. Patients with short PTI (0-6 days) had significantly worse overall survival from initiation of salvage therapy (median OS = 7.6 months, HR=2.10 (95% CI: 1.43-3.08) compared to patients who initiated therapy 7 or more days from progression (median OS = 29.7 months), logrank p<0.0001. This association remained consistent (HR=2.20, 95% CI: 1.48-3.26, p<0.0001) after adjusting for age and biopsy confirmation of progression. Short PTI was also associated with inferior response rate to initial salvage therapy (51% vs. 65%, p=0.058), lower rate of proceeding to transplant after initial salvage therapy (33% vs. 55%, p=0.0063), lower rate of being event-free 24 months from initial salvage therapy (16% vs 33%, p=0.011) and lower rate of ever proceeding to transplant (44% vs. 59%, p=0.057). Conclusions: A short progression-to-treatment interval is strongly associated with inability to proceed to transplant and inferior overall survival in r/r DLBCL. These results have implications for the design and interpretation of clinical trials in the relapsed/refractory setting. Figure. Figure. Disclosures Maurer: Celgene: Research Funding; Nanostring: Research Funding; Morphosys: Research Funding. Ansell:Trillium: Research Funding; Merck & Co: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Pfizer: Research Funding; Celldex: Research Funding; Takeda: Research Funding. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Cerhan:Nanostring: Research Funding; Celgene: Research Funding; Jannsen: Other: Scientific Advisory Board.

Purpose Despite lack of survival benefit, demand for contralateral prophylactic mastectomy (CPM) to treat unilateral breast cancer remains high. High uptake of CPM has been demonstrated in Midwestern rural women. Greater travel distance for surgical treatment is associated with CPM. Our objective was to examine the relationship between rurality and travel distance to surgery with CPM. Methods Women diagnosed with stages I–III unilateral breast cancer between 2007 and 2017 were identified using the National Cancer Database. Logistic regression was used to model likelihood of CPM based on rurality, proximity to metropolitan centers, and travel distance. A multinomial logistic regression model compared factors associated with CPM with reconstruction versus other surgical options. Results Both rurality (OR 1.10, 95% CI 1.06–1.15 for non-metro/rural vs. metro) and travel distance (OR 1.37, 95% CI 1.33–1.41 for those who traveled 50 + miles vs. < 30 miles) were independently associated with CPM. For women who traveled 30 + miles, odds of receiving CPM were highest for non-metro/rural women (OR 1.33 for 30–49 miles, OR 1.57 for 50 + miles; reference: metro women traveling < 30 miles). Non-metro/rural women who received reconstruction were more likely to undergo CPM regardless of travel distance (ORs 1.11–1.21). Both metro and metro-adjacent women who received reconstruction were more likely to undergo CPM only if they traveled 30 + miles (ORs 1.24–1.30). Conclusion The impact of travel distance on likelihood of CPM varies by patient rurality and receipt of reconstruction. Further research is needed to understand how patient residence, travel burden, and geographic access to comprehensive cancer care services, including reconstruction, influence patient decisions regarding surgery.

Background: Different survival metrics have different applicability to clinical practice and research. We evaluated how choice of survival metric influences assessment of cancer survival among American Indian and Alaska Native (AIAN) people relative to non-Hispanic Whites (NHW). A secondary objective was to present variations in survival among AIAN people by age, sex, stage, and Indian Health Service (IHS) region. Methods: Five-year survival was calculated using the North American Association of Central Cancer Registries Cancer in North America dataset. We calculated survival among AIAN people, compared with NHW using four approaches: (i) observed (crude) survival, (ii) cause-specific survival, (iii) relative survival using age- and sex-adjusted lifetables, and (iv) relative survival using lifetables additionally adjusted for race, geography, and socioeconomic status. For AIAN people, we evaluated how survival varied by age, stage at diagnosis, and IHS region. Results: Observed survival methods produced the lowest estimates, and—excepting prostate cancer—cause-specific methods produced the highest survival estimates. Survival was lower among AIAN people than NHW for all methods. Among AIAN people, survival was higher among those 20–64 years, females, and tumors diagnosed at local stage. Survival varied by IHS region and cancer sites. Conclusions: These results support the assertion that using the same methodology to compare survival estimates between racial and ethnic groups is of paramount importance, but that the choice of metric requires careful consideration of study objectives. Impact: These findings have the potential to impact choice of survival metric to explore disparities among AIAN people.

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