bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interest in cessation treatment and survival among smokers in a community-based multidisciplinary thoracic oncology program.
Authors: Meadows Meghan , Ward Kenneth Daniel , Faris Nicholas Ryan , Smeltzer Matthew , Fehnel Carrie , Ariganjoye Folabi , Smith Jessica , McHugh Laura , Fulford Angela , Osarogiagbon Raymond U. 
Published: May 2020

2028 Background: Tobacco cessation is essential to high quality oncology care. Many patients smoke when diagnosed and continue to smoke during treatment, which adversely affects treatment response and survival. Although most patients are motivated to quit, few receive effective cessation therapy. The multidisciplinary clinic (MDC), where patients, their caregivers, and key specialists coordinate care, is an ideal setting to integrate a cessation program. To assess the need for cessation services within a MDC setting, we surveyed incoming patients about their smoking status, interest in quitting, and willingness to participate in a clinic-based cessation program. Methods: The study was conducted in the Multidisciplinary Thoracic Oncology Program at Baptist Cancer Center, Memphis TN. We evaluated sociodemographic/clinical characteristics, smoking status, and tobacco dependence of consecutive new patients diagnosed with lung cancer from 2014-2019, who completed a social history questionnaire. Current smokers reported their interest in quitting and their willingness to participate in a cessation program. Chi square tests and logistic regression models were used to compare characteristics of those who would participate vs. those who would not/were unsure. Kaplan-Meier curves and multivariable Cox regression were used to evaluate the association between willingness to participate in a cessation program and overall survival, adjusted for age, sex, race, and total pack-years of smoking. Results: Of 641 patients, the average age was 69 years (range: 32-95), 47% were men, 64% white/34% black, and 17% college graduates; 90% had ever smoked, 34% currently smoked, and 24% quit smoking within the past year. Among current smokers, 60% were very interested in quitting and 37% would participate in a clinic-based cessation program. Willingness to participate was associated with greater interest in quitting (p = 0.0010) and greater overall survival (log rank p = 0.01;HR: 0.48, 95% CI: 0.24-0.95) but was not associated with any sociodemographic, clinical, or smoking-related characteristics. Conclusions: Over half (58%) of patients in a community-based MDC program were current smokers/recent quitters. Willingness to participate in a cessation program was associated with improved survival, suggesting patients with favorable prognoses are especially interested in receiving cessation support. There is considerable need for cessation services and relapse-prevention support within a coordinated, MDC lung cancer care setting.
Implementation of Symptom Care Clinic (SCC) for acute symptoms management at outpatient oncology ambulatory centers.
Authors: Xiao Han , Fahy Rosanna , Salvaggio Rori , OSullivan Maryellen , Sokoli Desiree , Murray Cheryl , Majeed Jibran , Mao Jun J. , Groeger Jeffrey S. 
Published: May 2020

2030 Background: With improved overall cancer survival, increasing number of cancer patients are undergoing active treatment. This, in return, add burden in acute symptom management related to disease and treatment. This has resulted in increasing unplanned emergency room (ER) visits and negatively impacted patients experience and health cost. We establish Symptom Care Clinic (SCC) embedded in suburban ambulatory oncology centers to reduce unplanned ER lists and to improve patient experience. Methods: Together with all stakeholders, we developed six SCCs at regional ambulatory centers in NY and NJ. Clearly defined work flow and algorithm were developed to ensure appropriate patient referral. On-site radiology and laboratory services are available. The SCCs are staffed with combination of Advanced Practice Provided (APP) and physicians or APP alone supported by on site medical oncologist or remote central Urgent Care Center Attendings. We evaluated clinic volumes, reduction ins unplanned ER visits and patient experience. Results: From October 2017 to December 2019, total of 17,542 SCC visits were documented. Total of 17,479 lab and 5,355 radiology tests as well as 3,915 infusions were performed. The top five most common laboratory tests are CBC, blood cultures, CMP, respiratory panel and urine culture. The most common symptoms are fever, nausea/vomiting/dehydration, rash and pain. Among all SCC visits during this period, 83% were discharged home and 17% were transferred to ER or hospitals. During 2019, total 10,736 SCC visits were recored, APP evaluated 73.7% of visits and physicians 16.3% with comaprable recidivism rate, 2.52% and 2.75%, respectively. Conservatively, we estimated that approximately 40% of visits would have been Er visits based on numbers of CBC and other testes performed. Qualitative feedbacks from patients indicated positive experience in convenient access, cohesive care coordination and time saving from traveling to and waiting in ER. Conclusions: We successfully implemented an effective acute symptom management system in busy ambulatory oncology centers that is patient centric. Out data showed that SCC reduced unplanned ER visits and that APP/physician model has low recidivism rate.
Effect of a supportive medicine program for cancer patients on patient connectivity to care and health care utilization.
Authors: Worster Brooke , Garber Gregory D. , Cammy Rebecca , Yocavitch Liana , Shimada Ayako , Csik Valerie Pracilio , Chapman Andrew E. , Leader Amy 
Published: May 2020

2034 Background: The benefits of supportive medicine (SM) for cancer patients include improved quality of life, increased patient satisfaction, improved symptom management, increased cost savings and improved survival rates. At one NCI-designated cancer center, all patients were screened for distress; those who screened positive or were directly referred by a provider were enrolled into our multi-disciplinary SM program. Here, we document the impact of the supportive medicine program on outcomes of emergency department (ED) visits, hospital readmission, and non-billable touchpoints associated with patient navigation and resource referrals. Methods: The program systematically screened for biopsychosocial distress utilizing the National Comprehensive Cancer Center Distress Thermometer (DT) and the Problem Checklist (PC) to identify practical, emotional, spiritual and physical issues. Patients were categorized into three types: screened and enrolled in the SM program, and screened and not enrolled in the SM program, or provider referral into the SM program. Data included patient’s age, number of hospital admissions, emergency department visits, and non-billable touchpoints at 90 and 180 days after the distress screening or referral. Descriptive data were analyzed with counts and percentages for categorical variables and summarized with mean and standard deviation for numerical variables. For investigation of the effects of time and patient type on the change in utilization rate, generalized estimation equations for Poisson regression were conducted for each outcome. Results: In all, 2,738 patients were included in the analysis. Patients who were referred from a provider tended to be younger (p < .01) and more likely to die within 90 days (p < .001). At 180 days, ED visits decreased 18% for patients referred to the SM program and 42% for patients screened into the SM program, compared to a 3% decrease in ED visits among those not enrolled in the SM program (p < .01). Similarly, hospital admissions decreased 34% for patients referred to and 39% screened into the SM program, compared to a 4% increase for patients not enrolled in the SM program (p < .01). Non-billable touchpoints increased among all types of patients. Conclusions: An SM program reduces hospital admissions and ED visits, therefore improving outcomes and potentially reducing the cost of care for cancer patients. Future research should link this data to claims data to definitely evaluate the impact of SM programs on cost.
Model selection applied to 750 outpatient ICD-9 codes identifies hazards important for all-cause cancer mortality in 2 million veterans with 14 years of follow-up.
Authors: McMahon Benjamin , Dhaubhadel Sayera , Hengartner Nicolas , Danciu Ioana , Janet Tate , Justice Amy 
Published: May 2020

2053 Background: Cost-benefit analysis before undergoing cancer treatments can involve a broad array of factors, yet existing statistical algorithms are limited to a few of the most commonly observed competing risks. Using 20 years of Veteran medical records from the Veteran’s Administration, we identify a broad array of outpatient descriptors providing contributions to computed mortality comparable in size to common cancers. Methods: 1,911,632 Veterans born between 1927 and 1968 with medical records extending from October 1, 2000 until either recorded death after October 1, 2005 (47%) or observation during CY 2019 were split equally into age-matched test and training sets. The 20 year-long record was split into three intervals: 5 years during which ICD codes were tallied, 14 years of waiting, and establishment of continuation in care during 2019. The 750 most common outpatient ICD9 codes were recorded as present/absent for each patient and used in a generalized linear model to predict subsequent mortality, subject to LASSO model selection and 10-fold cross validation. Gender was included as a covariate as well as age at time of prediction, up to the 4th power. Results: The C-statistic for predicting mortality in 14 years of follow-up was 0.835 on training data and 0.833 on test data when using the 498 codes selected by LASSO. Prevalent codes with the largest model coefficients were (ICD 9 code: model coefficient, # alive/# deceased in test set) congestive heart failure (428.0: 0.66, 9k/48k), chronic airway obstruction (496.: 0.60, 42k/105k), and tobacco use disorder (305.1: 0.54, 107k/123k), while the prevalent codes most protective in comparison to baseline were hyperlipidemia (272.4: -0.21, 211k/225k) and colon cancer screening (V76.51: -0.16, 49k/39k). In comparison, observed cancer ICD 9 coefficients were lung (162.9: 1.03, 1k/7k), colon (153.9: 0.18, 3.1k/7.0k), and prostate (185.: 0.06, 16k/32k). 74 predictors contribute with coefficients greater than colon cancers, such as ‘no household member able to render care’ (V60.4: 0.28, 1.1k/4.2k). Conclusions: A wide variety of structured data contribute at a similar level of importance in prediction of 14-year mortality. While various selection biases, co-linearity of predictors, differences in treatments, and missing data are significant impediments to utilization of predictive models in clinical practice, we have demonstrated an ability to identify and quantify predictors from a large data set with model selection techniques.
Core limitations in clinical trials leading to anticancer drug approvals by the U.S. Food and Drug Administration.
Authors: Hilal Talal , Gonzalez-Velez Miguel , Prasad Vinay 
Published: May 2020

2057 Background: To date, a comprehensive evaluation of core limitations in clinical trials leading to anti-cancer drug approvals by the US Food and Drug Administration (FDA) has not been undertaken.The aim of this analysis was to assess the percentage of clinical trials with core limitations, defined as lack of randomization, lack of overall survival data, inappropriate use of crossover, and use of sub-optimal control arms that led to FDA approvals from 2014 to 2019. Methods: This observational analysis included all approved anti-cancer drug indications by the FDA from July 2014 through July 2019. All indications were investigated and each clinical trial evaluated for design, enrollment period, primary endpoints, and presence of core limitations. The standard of care therapy was determined by evaluating the literature and published guidelines 1-year prior to start of clinical trial enrollment. Crossover was examined and evaluated for optimal use. We then calculated the percentage of approvals based on clinical trials with any or all core limitations. Results: A total of 187 anti-cancer approvals were evaluated. The number of anti-cancer drug approvals doubled over time with 68 in first half of study period (June 2014 to December 2016) to 119 in second half of study period (January 2017 to July 2019). Of those, 125 (67%) were based on a clinical trial with at least one core limitation. 64 (34%) approvals were based on a single-arm clinical trial. Of the remaining 123 approvals based on randomized trials, 60 (32%) had a core limitation. Of all randomized trials, 37 (30%) lacked overall survival benefit, 31 (25%) had a sub-optimal control, and 17 (14%) used crossover inappropriately. Conclusions: The majority of cancer drugs are approved based on clinical trials with core limitations. Efforts to minimize core limitations at the time of clinical trial design are essential to ensure that new anti-cancer drugs being marketed truly improve patient outcomes over current standards.
Gender-based disparities in clinical trials supporting FDA approval of oncology drugs.
Authors: Zettler Marjorie , Feinberg Bruce A. , Kish Jonathan , Gajra Ajeet 
Published: May 2020

2058 Background: Adequate gender representation in clinical trials of new drugs is critical in order to accurately detect possible differences in response and toxicity (Özdemir et al, JCO 2018). The under-representation of women in oncology clinical trials has been previously described, however data on registrational trials, which are the basis for drug approval and inform the prescribing information, is lacking. We conducted an analysis of the trials supporting Food and Drug Administration approval of oncology drugs over a 5-year period to evaluate the representation of women vs. men. Methods: Prescribing information for novel new drugs approved from 2014-2018 was reviewed for the proportions of men and women in the evaluable population of the supporting clinical trials. Sex-specific cancers were excluded. Prevalence estimates for the indications were obtained from the Surveillance, Epidemiology and End Results database and the published literature. A participation to prevalence ratio (PPR) was calculated for each trial by dividing the percentage of women in the trial by the percentage of women in the disease population. A PPR value closer to unity represents even gender distribution and the range 0.8-1.2 is considered to reflect an acceptable representation of women. Data are presented using descriptive statistics. Results: A total of 46 oncology drugs were approved based on 56 trials enrolling 13,862 patients (7941 [57%] men; 5,921 [43%] women). Of the 56 trials, 38 (68%) had a PPR within the 0.8-1.2 range, 15 (27%) fell between 0.4-0.7, and 3 (5%) had a PPR of 1.3. The proportion of trials with unbalanced gender representation was comparable for hematological malignancy and solid tumor indications and did not improve over time. Fewer unbalanced trials were Phase III or employed a randomized design. Nine of the 18 (50%) unbalanced trials enrolled <100 subjects, compared to 3 of the 38 (8%) balanced trials. Conclusions: A third of registrational trials for oncology drugs lacked balanced gender distribution. Of the trials lacking balance, the vast majority (80%) had under-representation of women. Phase I-II trials and smaller trials had greater gender disparity, a concerning finding in a precision medicine environment where an increasing number of registration trials have double digit accrual. Further research is needed to understand the implications of unbalanced gender accrual in registrational trials, and to develop strategies for preventing disparities.
Home ePRO compliance in prostate cancer clinical studies.
Authors: Gary Sarah Tressel , Dias Nadeeka , Conrad Elisa , Faulkner Kenneth G 
Published: May 2020

2063 Background: Patient-reported outcomes (PRO) and electronic PRO (ePRO) play an important role in the development and approval of cancer products. Regulatory agencies are encouraging the inclusion of PRO-based endpoints that are indicative of clinical benefit in terms of patient symptoms and overall quality of life (QOL). Compliance with completion of ePRO assessments is an important component for obtaining accurate and high-quality data when conducting clinical trials. Traditionally, ePRO data in oncology trials has been collected mainly at clinic visits due to concerns over poor compliance at home. However, since symptoms and QOL can vary widely through a treatment course, it is often necessary to collect ePRO data more frequently in between clinic visits. It has been hypothesized that home completion, length of time in a study, and number of assessments may affect compliance. Methods: To address this hypothesis, ePRO compliance data was analyzed from two clinical studies in prostate cancer. Both studies used a handheld smartphone that contained an application to collect ePRO data. At the randomization visit, subjects completed ePRO assessments in clinic (2-3 questionnaires). Subsequently, all assessments were completed at home, including a daily diary and 1-4 questionnaires completed every 4-8 weeks for up to 14 months. Compliance was calculated as the number of assessments received divided by the number of assessments expected in a given assessment period. To evaluate assessment burden, each assessment period was categorized as requiring a lower number (daily diary and 1 questionnaire) or higher number (daily diary and 2-4 questionnaires) of assessments. Results: A total of 1,040 patients were included in the analysis. Overall compliance at the single clinic visit was 100%, which was expected since it was a required randomization visit. Overall compliance at home over 14 months was 80%. Compliance ranged from 78% to 89% over the duration of the studies, with no effect of time in the study on compliance. Compliance remained high even as patient numbers declined. Compliance when patients were required to complete a lower number of assessments (80%) was similar to compliance when patients were required to complete a higher number of assessments (79%). Compliance by region varied from 72% (Middle East) to 87% (Asia and Eastern Europe). Conclusions: The collection of ePRO at home provided high compliance that did not vary with length of time in the study or due to assessment burden. At home ePRO assessments provide an effective and feasible approach for recording symptoms and QOL in prostate cancer patients.
Timing of US Food and Drug Administration (FDA) cancer drug approvals relative to publication of clinical trial results.
Authors: Khaki Ali Raza , Desai Aakash , Schoen Martin W. , Gyawali Bishal , Chen Eddy J. , Yang Peter C. , Warner Jeremy Lyle 
Published: May 2020

2071 Background: Publication of clinical trial results in peer reviewed literature is essential to inform clinicians regarding the use of new anti-cancer treatments, which often have a low therapeutic ratio and require careful assessment of risks and benefits. Publication of registration trials should precede FDA approval to facilitate evaluation and implementation of new therapies. The timing of trial publication relative to FDA drug approvals has not been systematically investigated. Methods: We collected all FDA drug approvals for a cancer indication between 2000-19. Trials were identified using FDA labels as well as drugs and publications indexed on HemOnc.org. Approvals for generics/biosimilars, non-oncology indications and label revisions without supportive evidence were excluded. Dates of approval, the approval pathway, approval type (new vs expansion), and the first full publication related to the registration were recorded. Trials and approvals were matched using available metadata. We calculated the proportion of drugs approved prior to publication overall and for those receiving accelerated approval (AA). We used logistic regression to compare rates of pre-publication approval by approval pathway and by new vs expanded approval. Results: Among a total of 378 drug approvals, 139 (37%) had pre-publication approval. Of these, the median overall time from approval to publication was 140 days (IQR 64-281 days). For those with approval after publication, median time from publication to approval was 157 days (IQR 72-359 days). The number of drugs approved pre-publication rose by 27% between the first and last quarters of the study period, though, the proportion decreased as more anti-cancer drugs have been approved in recent years (Table). More drugs were approved pre-publication through AA than regular approval (46% vs 34%, OR 1.66 [95% CI 1.03-2.70], p=0.04) and as new approvals vs. expanded approvals (45% vs 32%, OR 1.76 [95% CI 1.15-2.70], p=0.01). Conclusions: A substantial minority of FDA approvals occur before trial results are published, with the odds being higher for drugs receiving AA and for new approvals. Since clinicians rely upon published results to inform risk/benefit decisions, efforts are needed to ensure trial results are published by the time of FDA approval of new cancer drugs and indications. [Table: see text]
The clinical impact of ASCO “choosing wisely” recommendations on staging imaging for early stage breast cancers: An interrupted time-series analysis utilizing SEER-Medicare data.
Authors: Baltz Alan , Makhoul Issam , Siegel Eric R 
Published: May 2020

2078 Background: The “Choosing Wisely” (CW) list, released by the American Society for Clinical Oncology (ASCO), highlights low-value procedures. In 2012, the CW recommendations advised against the use of staging imaging, including Positron Emission Tomography (PET), Computerized Tomography (CT) and radionuclide bone scans, for the staging of early breast cancer at low risk for metastasis. The objective of this study was therefore to assess the impact of the ASCO CW recommendations on staging imaging among early stage breast cancers. Methods: Women above the age of 66 with an early stage incident breast cancer diagnoses between 2010 and 2015 were identified within the linked SEER-Medicare data. The primary outcome of interest was the proportion of patients with a claim for staging imaging in the six months following the breast cancer diagnosis. Negative binomial regression, adjusting for pre-recommendation trends, was performed to estimate the changes in the rate of imaging staging within each year following the release of the recommendation. Results: A total of 50,004 women were identified during the study period. Prior to the release of the recommendations in 2012, the staging imaging rates among women newly diagnosed with early stage breast cancers were 5% greater in 2010 (p<.01) and 4% greater in 2011 (p<.01). Following the release of the recommendations, staging imaging rates did not decrease significantly in 2013 (2%;p=0.18). Imaging rates did, however, significantly decrease by 13% in 2014 (p<0.01) and by 16% in 2015 (p<0.01). Conclusions: The CW recommendation was associated with a significant decrease in unadvised staging imaging among incident early stage breast cancer diagnosis in the second and third year following its release. These findings demonstrate an improvement in the proportion of potentially inappropriate staging imaging in early stage breast cancers. The creation and dissemination of resources, such as the CW recommendations, serves as a powerful tool to improve clinical practice, quality of care, and patient safety from secondary malignancies, anxiety, and overdiagnosis.