bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of comorbidity measures to predict postoperative lung cancer survival in the National Cancer Database (AFT-03).
Authors: Wong Melisa L. , McMurry Timothy L. , Stukenborg George J. , Francescatti Amanda B. , Amato-Martz Carla , Schumacher Jessica R. , Greenberg Caprice Christian , Chang George J. , Winchester David P , McKellar Daniel P. , Walter Louise Christie , Kozower Benjamin D. 
Published: September 2018

6519 Background: Comprehensive assessment of comorbidity in cancer registries is critical for comparative effectiveness research. The National Cancer Database (NCDB) measures comorbidity with a diagnosis code-based Charlson Comorbidity Index (CCI) abstracted from discharge abstracts or billing face sheets. However, the prognostic performance of this code-based CCI has not been compared with a medical chart-based CCI or individual comorbid conditions in a nationally representative sample of patients with lung cancer. Methods: Through a special study of the NCDB, cancer registrars performed chart abstraction for 18 perioperative comorbid conditions for 9,640 randomly selected patients with stage I-III non-small cell lung cancer resected in 2006-07 at 1,150 Commission on Cancer-accredited facilities. We compared the prognostic performance of the NCDB code-based categorical CCI (0, 1, 2+), special study chart-based continuous CCI, and individual comorbid conditions in 3 separate Cox proportional hazards models for 5-year postoperative overall survival. All models adjusted for demographic and clinical characteristics. Results: Median age was 67 (IQR 60-74). The most common comorbidities were COPD (40%) and CAD (21%). Five-year postoperative overall survival was 55.5%. Agreement between the code- and chart-based CCIs was 51.9% with the code-based CCI underestimating comorbidity for 36.2% patients. The model including individual comorbid conditions had the best prognostic performance (R2 0.196, C index 0.654). COPD, CAD, CHF, dementia, diabetes, moderate/severe renal and liver disease, peripheral vascular disease, psychiatric disorder, and substance abuse were independently associated with decreased survival. The chart-based CCI model (R2 0.189, C index 0.650) predicted postoperative survival better than the code-based CCI model (R2 0.181, C index 0.645). Conclusions: The NCDB code-based CCI underestimates comorbidity in patients with surgically resected lung cancer. The chart-based CCI and data on individual comorbid conditions improved prognostic performance and would be valuable additions to the NCDB to strengthen comparative effectiveness research.
Changes in insurance coverage associated with health care reform for cancer survivors aged 19-64 years.
Authors: Davidoff Amy J. , Guy Gery P , Hu Xin , Gonzales Felisa A , Han Xuesong , Zheng Zhiyuan , Ekwueme Donatus U. , Jemal Ahmedin 
Published: September 2018

6527 Background: Beginning in 2014, Medicaid eligibility was expanded in over half of states, enrollment was simplified, and insurance marketplaces were created in all states with premium subsidies for selected individuals, as a result of implementation of the Affordable Care Act (ACA). We examine changes in insurance coverage for cancer survivors overall, and for targeted subgroups affected by specific ACA elements. Methods: We pooled data for cancer survivors aged 19-64 years from the 2012-2015 National Health Interview Survey. Using information on family structure, income, and employment, and linked state-specific Medicaid eligibility policies, we assigned survivors to 3 targeted groups: 1) Medicaid eligible pre-ACA; 2) Medicaid expansion eligible; 3) eligible for premium tax credits for Marketplace plans; and 3 groups not targeted for benefit: a) eligibility gap (income < 100% federal poverty level (FPL) in states not expanding Medicaid); b) with alternative “affordable” coverage; and c) high income ( > 400% FPL). Linear probability regressions examined pre(2012-13)/post(2014-15) coverage changes by eligibility category, adjusting for demographic characteristics. Results: Among 4,115 (wtd N = 6.90M) cancer survivors, insurance pre-ACA was 69% private, 15.2% public, and 12.2% uninsured. Post-ACA, overall public coverage increased by 3.2 percentage points (pct pt) (p = .036), whereas the percent uninsured decreased by 4.5 pct pt (p < .001). Relative to the high income category, the adjusted percent uninsured decreased by 8.4 pct pt (95% CI:1.2-15.5) among pre-ACA Medicaid eligible, by 16.7 pct pt (95% CI:8.9-24.4) among the newly Medicaid eligible, and by 11.3 pct pt (95% CI:1.0-23.4; p = .069) among premium subsidy eligible. No coverage gains were observed for the other 2 categories. Approximately 531,000 cancer survivors remained uninsured after ACA implementation, with over half eligible for either Medicaid (12%) or subsidized Marketplace plans (44%). Conclusions: In the first 2 years post-ACA, cancer survivors experienced substantial increases in insurance coverage, with changes limited to targeted subgroups. Over half of remaining uninsured were eligible for coverage.
Validation of natural language processing (NLP) for automated ascertainment of EGFR and ALK tests in SEER cases of non-small cell lung cancer (NSCLC).
Authors: Goulart Bernardo H. L. , Silgard Emily , Baik Christina S. , Bansal Aasthaa , Greenwood-Hickman Mikael Anne , Hanson Annika , Ramsey Scott David , Schwartz Stephen 
Published: September 2018

6528 Background: The Surveillance, Epidemiology, and End Results (SEER) registries lack information on the Epidermal Growth Factor Receptor (EGFR) mutation and Anaplastic Lymphoma Kinase (ALK) gene rearrangement test results. With the goal of enabling population-based outcomes research in molecularly selected NSCLC subgroups, we conducted a validation study of NLP for ascertainment of EGFR and ALK testing from electronic pathology reports (e-paths) of patients included in the Seattle-Puget Sound (SPS) and Kentucky Cancer (KCR) SEER registries. Methods: We obtained 4,278 and 1,041 e-paths pertaining to 1,634 and 565 patients with stage IV non-squamous NSCLC diagnosed from 1/1/2011 to 12/31/2013 and included in the SPS and KCR registries, respectively. Two oncologists independently reviewed all reports to generate a gold-standard dataset. We used 855 of the SPS reports to train hybrid rule-based and machine learning algorithms for detection of test status (reported vs. not reported), and test result if reported (positive vs negative) for EGFR mutational analysis and ALK testing by FISH, IHC, or gene sequencing. In the remaining 3,423 SPS reports, we conducted a 5-fold cross-validation analysis to estimate the internal NLP sensitivity, specificity, positive predictive value, and negative predictive value for test status and results, respectively. We used a hierarchical rules system to assess the NLP accuracy at the patient level. For external validation, we repeated all analyses in the KCR dataset. Results: In the SPS internal validation report sample, the validity metrics ranged from 97% to 99% for EGFR and ALK test status, and from 95% to 100% for EGFR and ALK test results, respectively. In the KCR external validation report sample, the metrics ranged from 74% to 96% for EGFR and ALK test status, and 2% to 100% for test results, respectively. At the patient level, the NLP accuracy for EGFR and ALK was 95% and 96% (SPS cohort), and 70% and 72% (KCR cohort) respectively. Conclusions: NLP is a valid method for determining EGFR and ALK test status and results for patients included in SEER registries with access to e-path, but the algorithms likely need to be registry-specific.
Financial conflicts of interest at three prominent oncology clinical pathway vendors.
Authors: Daly Robert Michael , Bach Peter , Page Ray D. 
Published: September 2018

6529 Background: The American Society of Clinical Oncology (ASCO) reports that in 2015 62% of oncology practices are adhering to a clinical pathway and 31% are adhering to more than one pathway. ASCO and the American Medical Association have raised concerns about the conflicts of interest of those that design these pathways. Methods: Using the public Centers for Medicare and Medicaid Services Open Payments database, we abstracted the 2015 financial conflicts of interest for the 2016 voting members of the Value Pathways (a combined effort of US Oncology and NCCN), the medical oncology committee chairs for Via Oncology, and the medical advisory board for eviti. We focused on national pathway vendors and on non-research general payments, such as gifts, consulting, and speaker fees. Results: Nearly all involved in pathway development received non-research general payments in 2015, including 92% of US oncology, 84% of NCCN, 84% of Via Oncology, and 69% eviti. The average general payments ranged from $3.5K for US Oncology Value Pathways voting members to $15.3K for NCCN Value Pathways voting members. Eight percent of US Oncology voting members, 19% of the eviti medical advisory board, 28% of Via Oncology chairs, and 42% of NCCN voting members received $10,000 or more in general payments in 2015. Conclusions: Given the prominent role clinical pathways have on oncologists’ prescribing behavior and the often subjective nature of determining on-pathway treatment, pathway vendors should take care to make accessible their conflict of interest policies and elucidate how they manage relationships of concern.Steps would include potentially limiting the number of committee members receiving payments and limiting the amount of general payments to each physician.
Thirty-day readmissions in metastatic cancer patients: Room for improvement?
Authors: Solomon Rachel , Egorova Natalia , Franco Rebeca , Bickell Nina A. 
Published: September 2018

6541 Background: To date, cancer has been excused from most readmission reduction efforts. Yet reported readmission rates for cancer patients discharged from medical services are as high as 27%. Some readmissions for patients with metastatic disease may be avoidable. We assessed the prevalence of potentially preventable readmissions and associated factors in adult patients with metastatic cancer. Methods: We measured 30 day readmissions for dehydration, cancer-related pain, and failure to thrive in patients with primary diagnosis metastatic cancer on index admission to a New York State hospital between December 1, 2012 and December 31, 2014. We used competing risk models to assess the effects of demographics, comorbidities, hospital type, payor, and discharge disposition. Results: During the study period, 11,275 patients had 19,307 index hospitalizations with primary diagnosis, metastatic cancer. The 30 day readmission rate was 24.5% of which 8.9% (424) were potentially preventable. Black (HR 1.26, 1.17-1.35) and Hispanic patients (HR 1.19, 1.09-1.31) had higher rates of readmission than whites. Being older (HR per 10 years of age 0.94, 0.90-0.97), female (HR 0.95, 0.91-0.99), having private insurance (HR 0.87, 0.87-0.81) and discharge to hospice (HR 0.62, 0.42-0.91) decreased risk of readmission. Discharge home with services (HR 1.21, 1.14-1.27) or to a skilled nursing facility (SNF) (HR 1.11, 1.01-1.23) conferred higher risk than going home unaided. Index hospitalization at public hospitals increased risk (HR 1.1, 1.02-1.18); teaching hospitals were protective (HR 0.84, 0.774-0.92). Patients with potentially preventable readmissions were younger (HR per 10 years of age 0.85, 0.78-0.93). Compared to those who went home unaided, patients discharged with services were more likely (HR 1.31, 1.05-1.64) and those discharged to SNF were less likely to have avoidable returns (HR 0.55, 0.37-0.81). Payor, gender, race, comorbidities, and index hospital type did not contribute. Conclusions: While the overall rate of potentially preventable admissions among metastatic cancer patients is low, higher readmission rates among those discharged home with help suggests that services supplied are not sufficient to address their health needs.
National coverage analyses for NCI clinical trials: A pilot project to reduce participation barriers.
Authors: Denicoff Andrea , Mishkin Grace , Good Marjorie J. , Patrichuk Lucille , Ragard Lawrence , Hurtado Kathleen R , Willenberg Kelly , Szczepanek Connie M. , Dawson Casey , Alexander-Young Morgen , Strandberg Debra L , Kardell Julie , McCartney Sara , Sullivan Mary Beth , Kelly Michael , Montello Michael , McCaskill-Stevens Worta J. , Abrams Jeffrey S. , Mooney Margaret M. ,   NCI Coverage Analysis Working Group
Published: September 2018

6542 Background: Since the implementation of the ACA, many insurers have followed Medicare’s lead in covering routine care costs associated with clinical trials (CTs). However, questions remain on how to distinguish routine care from non-billable research costs, and this has important financial implications for both sites and patients. As a result, many sites individually conduct coverage analyses (CAs) prior to opening CTs to determine billable routine costs. This is a significant duplication of effort for NCI network CTs that are open at hundreds of sites. A 2015 ASCO-NCI initiative identified the centralized creation of CAs for national CTs as a potential solution to reduce site burden, increase CT transparency and billing compliance, and ultimately reduce barriers to CT participation. We provide initial findings from the resulting NCI pilot program. Methods: NCI set up a Coverage Analysis Working Group (CAWG) made up of representatives from NCI’s Cancer Trials Support Unit (CTSU), network groups, NCI, and billing compliance consultants. CAWG created a CA template and development process for NCI network trials. CAWG will survey site users in April 2017 to evaluate the first year of the pilot project. Results: CAs for 7 CTs were first posted to the CTSU website on 4/20/16. As of January 2017, CAs have been posted for 22 CTs: 17 NCTN and 5 NCORP. This represents 14.6% of the 150 large, later-phase network trials available on the CTSU. These CAs had been posted for a mean of 219 days (median 238) as of 1/31/17. In this time, CAs were downloaded an average of 319 times (median 301), for a total of 7,007 downloads. An additional 26 CAs have been posted for MATCH (n = 20) and LUNG-MAP (n = 6) sub-studies and downloaded 7,035 times. Survey results evaluating this CA pilot will be presented in June 2017. Conclusions: Providing centralized CAs to NCI’s national network trials is feasible and well received with sites reporting that this pilot is reducing the time and effort of opening CTs and improving CT funding transparency. Collaboration is needed with CMS and third party payers to enhance clarity around CT coverage policy and billing compliance, along with continued feedback to make further improvements to reduce trial barriers.
Assessing performance status and clinical outcomes with wearable activity monitors.
Authors: Gresham Gillian K. , Neeman Elad , Hendifar Andrew Eugene , Li Quanlin , Tuli Richard , Rimel Bj , Walsh Christine S. , Spiegel Brennan , Figlin Robert A. , Piantadosi Steven , Shinde Arvind Manohar 
Published: September 2018

6571 Background: Performance status (PS) is assessed to inform treatment decisions and predict outcomes in cancer. PS is often evaluated using ECOG or KPS scales, limited by their subjective and static nature. Wearable activity monitors provide oncologists with the opportunity to obtain continuous objective data on patients’ daily activity including steps, stairs climbed, and sleep. We evaluated the association between wearable activity monitor data, PS, and clinical outcomes. Methods: Patients with advanced cancer were enrolled in a prospective, observational study conducted at Cedars-Sinai Medical Center. Patients wore a Fitbit Charge HR for 3 consecutive clinic visits. ECOG/KPS were rated by treating physicians and serious adverse events (AE, clinically relevant grade 3+ by CTCAE v4), hospitalizations, and 6-month survival were collected. Correlations between PS and activity metrics were calculated. Multivariable regression models were fit to predict AEs and hospitalizations with activity data. The association between activity metrics and time to death was evaluated using survival analysis. Results: 35 patients (median age 62 years, 53% male) were evaluated. Most had gastrointestinal cancers (82%). Patients had ECOG PS of 0 (20%), 1 (40%), 2 (23%), and 3(17%). There were 10 (29%) pts with serious AEs, 14 (40%) hospitalizations, and 11 (31%) deaths. Average daily steps were significantly correlated with ECOG PS and KPS (r=0.73 and 0.70, respectively). Relationships between activity metrics, AEs, hospitalizations, and overall survival (OS) are displayed in the table below. Conclusions: We found a significant association between wearable activity monitor data and the risk of AEs, hospitalization and death. There is a strong correlation between step counts and KPS/ECOG PS. The potential of wearable activity data to predict outcomes and supplement PS assessment should be explored in future studies. Clinical trial information: NCT02659358. [Table: see text]
Does coaching goals of care discussion skills make a difference?
Authors: Bickell Nina A. , Adelson Kerin B. , Gonsky Jason Parker , Pintova Sofya , Levy Benjamin Philip , Lin Jenny J. , Franco Rebeca , Egorova Natalia , Smith Cardinale B. 
Published: September 2018

6586 Background: Advanced cancer patients often have a poor understanding of their cancer prognosis. Goals of Care (GoC) discussions provide information about the cancer, its treatment & prognosis and elicit patient values. Little is known about the best ways to enhance patient understanding, clarify values and move GoC discussions earlier in the disease process. We report the effect of coaching oncologists on GoC discussions. Methods: We recruited oncologists & their advanced cancer patients with < 2 year prognosis to a RCT testing a coaching model communication skills training. Patients were surveyed after their post-imaging visit. We define GoC discussions as patient report that their doctor talked about their cancer prognosis and clarified things most important to them given their disease. Outcome variables assess the impact of GoC on patients’ knowledge on what to expect and clarity of values. Results: We enrolled 22/25 (88%) oncologists and 70% of eligible patients of whom 96 (55%) completed a survey. On average, doctors were 44 yrs old (32-66) and in practice 14.5 yrs (5-40). Patients’ mean age was 62 yrs (20-95), 40% females, 58% white, 24% Latino & 22 % black. Overall, 2/3 of patients reported their treatment’s goal was to cure their cancer; 14% reported cure to be unlikely. Patients felt more knowledgeable (79% vs 21%; p = 0.02) when their doctors discussed treatments, side effects & quality of life. When patients were asked about things important to them, they report being a bit clearer about their values (65% vs 35%; p = 0.16). Compared to controls, intervention patients felt more knowledgeable (78% v 63%; p = 0.17) but did not feel clearer about their values (60% v 54%; p = 0.59). Multivariate modeling found that poor health literacy (OR = 0.2; 95%CI: 0.07-0.82), having a GoC discussion (OR = 10.2; 1.7-63.1) and being in the intervention group (OR = 8.8; 1.4-55.2) significantly affected knowledge (model c = 0.88; p < 0.01). However, discussing what’s important to patients did not help patients feel clearer about their values (OR = 2.7; 0.6-12.2; model c = 0.82; p < 0.05). Conclusions: Using a coaching model to teach oncologists communication skills may improve patients’ understanding of what to expect with their cancer but does not impact their clarity of values. Clinical trial information: NCT02374255.
Implementing cost transparency in oncology: A qualitative study of barriers, facilitators, and patient preferences.
Authors: Aakhus Erin , Rosenstein Abigail , Joffe Steven , Bradbury Angela R. 
Published: September 2018

6597 Background: As cancer drug prices rise and insurance plans shift toward greater cost sharing, studies link patients’ high out-of-pocket (OOP) costs to non-adherence and early discontinuation of treatment. Meanwhile, few oncologists routinely discuss OOP costs with their patients. Using qualitative methods, we explored barriers and facilitators of cost transparency (i.e., disclosure of financial risks of cancer treatment). Methods: We performed semi-structured interviews with cancer patients (n = 22) and providers (n = 19) at an academic medical center and three affiliated community practices between August, 2015 and May, 2016. Two analysts coded the transcribed interview data using textual thematic methods, and hypotheses were generated employing grounded theory method. Results: We grouped themes that emerged into three major domains: 1) barriers, 2) facilitators, and 3) patient preferences. Patients and providers both expressed a strong aversion to making tradeoffs between financial and physical health outcomes. While patients feared being “profiled” based on their ability to pay, providers feared that cost transparency might threaten the doctor-patient relationship by exposing personal or institutional financial conflicts of interest. Pragmatic barriers included time constraints and difficulty in providing accurate cost estimates. Important facilitators were strong doctor-patient relationships and availability of support staff with financial expertise. We detected substantial heterogeneity in patient preferences. While some patients wanted to discuss costs with their provider, others feared “distracting” providers from their primary roles as health advocates. Conclusions: With implementation of OOP cost transparency, oncology practices will need to consider patient/provider aversion to financial/health tradeoffs, patients’ sensitivity to socioeconomic “profiling,” provider- and practice-level financial incentives, time constraints, accuracy of cost estimates, and variability in patient preferences. Meanwhile, strong provider-patient relationships and availability of support staff will facilitate OOP cost transparency.