SARS-CoV-2 Infection and Related Hospitalization among Cancer Survivors.

BACKGROUND: Little is known about SARS-CoV-2 infection and COVID-19 severity among a growing population of cancer survivors. We describe the association of infection and related hospitalization by recency of cancer diagnosis in a large U.S. cohort. METHODS: Participants were sent electronic surveys between April 2020 and January 2021 to collect information on SARS-CoV-2 infection and potential COVID-19-related risk factors. SARS-CoV-2 infections were identified using survey report of a COVID-19-positive test and electronic health record data. Cumulative incidence of SARS-CoV-2 infection was estimated up to 365 days from baseline survey and stratified by recency of cancer diagnosis. Among those with SARS-CoV-2 infection, we used logistic regression to estimate the association between recency of cancer diagnosis and hospitalization within 30 days of infection. RESULTS: Cumulative incidence of SARS-CoV-2 infection at 365 days was 3.3% [95% confidence interval (CI), 3.2%-3.5%] among those without cancer history and ranged from 2.8% (95% CI, 2.3%-3.5%) to 3.7% (95% CI, 2.9%-4.7%) among those with a history of cancer depending on recency. There was no statistically significant difference in odds of hospitalization within 30 days following SARS-CoV-2 infection by cancer diagnosis recency. CONCLUSIONS: Our null findings are consistent with other studies on COVID-19 infection risk in cancer survivors, where COVID-19 severity and sequelae were independent of cancer history and were likely associated with factors such as intensive care unit admission, noncancer comorbid conditions, and long-term care residency. IMPACT: This study can inform COVID-19 risk-counseling of cancer survivors and their caregivers as we continue to contend with COVID-19.

Evaluating cancer genetic services in a safety net system: overcoming barriers for a lasting impact beyond the CHARM research project.

Underserved patients face substantial barriers to receiving cancer genetic services. The Cancer Health Assessments Reaching Many (CHARM) study evaluated ways to increase access to genetic testing for individuals in underserved populations at risk for hereditary cancer syndromes (HCS). Here, we report the successful implementation of CHARM in a low-resource environment and the development of sustainable processes to continue genetic risk assessment in this setting. The research team involved key clinical personnel and patient advisors at Denver Health to provide input on study methods and materials. Through iterative and collaborative stakeholder engagement, the team identified barriers and developed solutions that would both facilitate participation in CHARM and be feasible to implement and sustain long term in clinical care. With a focus on infrastructure building, educational modules were developed to increase awareness among referring providers, and standard methods of identifying and managing HCS patients were implemented in the electronic medical record. Three hundred sixty-four DH patients successfully completed the risk assessment tool within the study, and we observed a sustained increase in referrals to genetics for HCS (from 179 in 2017 to 427 in 2021 post-intervention). Implementation of the CHARM study at a low-resourced safety net health system resulted in sustainable improvements in access to cancer genetic risk assessment and services that continue even after the study ended.Trial registration NCT03426878.

Developing an algorithm across integrated healthcare systems to identify a history of cancer using electronic medical records.

OBJECTIVE: Tumor registries in integrated healthcare systems (IHCS) have high precision for identifying incident cancer but often miss recently diagnosed cancers or those diagnosed outside of the IHCS. We developed an algorithm using the electronic medical record (EMR) to identify people with a history of cancer not captured in the tumor registry to identify adults, aged 40-65 years, with no history of cancer. MATERIALS AND METHODS: The algorithm was developed at Kaiser Permanente Colorado, and then applied to 7 other IHCS. We included tumor registry data, diagnosis and procedure codes, chemotherapy files, oncology encounters, and revenue data to develop the algorithm. Each IHCS adapted the algorithm to their EMR data and calculated sensitivity and specificity to evaluate the algorithm's performance after iterative chart review. RESULTS: We included data from over 1.26 million eligible people across 8 IHCS; 55 601 (4.4%) were in a tumor registry, and 44848 (3.5%) had a reported cancer not captured in a registry. The common attributes of the final algorithm at each site were diagnosis and procedure codes. The sensitivity of the algorithm at each IHCS was 90.65%-100%, and the specificity was 87.91%-100%. DISCUSSION: Relying only on tumor registry data would miss nearly half of the identified cancers. Our algorithm was robust and required only minor modifications to adapt to other EMR systems. CONCLUSION: This algorithm can identify cancer cases regardless of when the diagnosis occurred and may be useful for a variety of research applications or quality improvement projects around cancer care.

The Kaiser Permanente Research Bank Cancer Cohort: a collaborative resource to improve cancer care and survivorship.

BACKGROUND: The Kaiser Permanente Research Bank (KPRB) is collecting biospecimens and surveys linked to electronic health records (EHR) from approximately 400,000 adult KP members. Within the KPRB, we developed a Cancer Cohort to address issues related to cancer survival, and to understand how genetic, lifestyle and environmental factors impact cancer treatment, treatment sequelae, and prognosis. We describe the Cancer Cohort design and implementation, describe cohort characteristics after 5 years of enrollment, and discuss future directions. METHODS: Cancer cases are identified using rapid case ascertainment algorithms, linkage to regional or central tumor registries, and direct outreach to KP members with a history of cancer. Enrollment is primarily through email invitation. Participants complete a consent form, survey, and donate a blood or saliva sample. All cancer types are included. RESULTS: As of December 31, 2020, the cohort included 65,225 cases (56% female, 44% male) verified in tumor registries. The largest group was diagnosed between 60 and 69 years of age (31%) and are non-Hispanic White (83%); however, 10,076 (16%) were diagnosed at ages 18-49 years, 4208 (7%) are Hispanic, 3393 (5%) are Asian, and 2389 (4%) are Black. The median survival time is 14 years. Biospecimens are available on 98% of the cohort. CONCLUSIONS: The KPRB Cancer Cohort is designed to improve our understanding of treatment efficacy and factors that contribute to long-term cancer survival. The cohort's diversity - with respect to age, race/ethnicity and geographic location - will facilitate research on factors that contribute to cancer survival disparities.

Extent of diagnostic inquiry among a population-based cohort of patients with cancer of unknown primary.

PURPOSE: Current cancer registry data cannot distinguish a justified cancer of unknown primary (CUP) diagnosis, where the patient received a complete diagnostic evaluation that was unable to identify the primary tumor, from potentially misclassified patients, documented as CUP but not based on a complete diagnostic evaluation. This misclassification may skew population-based cancer registry surveillance research used to frame and guide translational CUP research. We identified characteristics of patients who received justified vs. potentially misclassified CUP diagnoses in cancer registry data. METHODS: We developed a conceptual definition of a complete diagnostic evaluation from professional society-recommended guidelines. We translated this definition into procedure codes in the Medicare encounter data. We assessed age, gender, comorbidities, urban or rural residence, income, race, and tumor pathology by receipt of a complete diagnostic evaluation and palliative therapy among 10,575 elderly CUP patients in the Surveillance, Epidemiology, and End Results (SEER)-Medicare dataset. We calculated odds ratios and adjusted probabilities using marginal standardization. RESULTS: Only 35% of elderly CUP patients identified in the cancer registry received a complete diagnostic evaluation. After adjustment for age and comorbidities, socioeconomic barriers to a complete diagnostic evaluation persisted: adjusted odds ratio and 95% confidence interval (AOR) for rural vs. urban 0.8(0.8,0.9) and for highest income vs. lowest income 1.2(1.1,1.4). Patients with vague or undocumented tumor pathology in SEER had 80% lower odds of receiving a complete diagnostic evaluation AOR(95%CI)=0.2(0.2,0.2). Although patients with a complete diagnostic evaluation were twice as likely to receive palliative therapy than those without a complete evaluation, AOR(95%CI)=2.0(1.7,2.3), they only had a 46.7% probability of receiving therapy, 95%CI=(44.4,49.1). CONCLUSION: Patients without a complete diagnostic evaluation are not limited to the frail and underserved. For accurate assessment of the CUP burden and disparities in utilization of diagnostic care, we recommend that the SEER definition of CUP include the extent of diagnostic inquiry.

Scope-of-practice laws and expanded health services: the case of underserved women and advanced cervical cancer diagnoses.

BACKGROUND: Underserved women (rural, minority or poor) are disproportionally diagnosed with late-stage cervical cancer, indicative of inadequate access to, and use of, preventative healthcare. The Institute of Medicine (IOM) has proposed that nurse practitioners (NP) can address provider shortages among underserved populations, but to reduce shortages, scope-of-practice laws that restrict the delivery of care, must be revised. We examined the IOM recommendation of NP expanded scope-of-practice laws on reducing the disparity of underserved women diagnosed with late-stage cervical cancer. METHODS: We examined the cohort of 10 673 women diagnosed with cervical cancer between 2010 and 2014 and reported to the Surveillance, Epidemiology and End Results cancer registry. We linked state-level laws regarding NP scope-of-practice to patients with cancer by their state of residence, diagnosis date and law enactment date. Hierarchical regression was used to explore NP full scope-of-practice law's impact on late-stage cancer diagnoses considering the moderating effect of women living in medically underserved areas. We adjusted for known confounders available in this population-based data set. RESULTS: Medically underserved women living in states with laws that restrict NP full scope-of-practice are twofold more likely to be diagnosed with late-stage cancer; adjusted OR and 95% CI (OR 2.08, 95% CI 1.4 to 3.1). These disparities were not observed among underserved women living in areas with NP full scope-of-practice laws (OR 0.95, 95% CI 0.7 to 1.3). CONCLUSIONS: NP full scope-of-practice laws could provide a pragmatic and cost-effective solution to healthcare provider shortages associated with late stage of cervical cancer diagnoses among underserved women.