tbuckley/cabot-search huggingface dataset:
Opioid prescribing trends and pain scores among adult patients with cancer in a large health system.
Authors: Laura Van Metre Baum, Pamela R. Soulos, Madhav KC, Molly Jeffery, Kathryn Jean Ruddy, Catherine C. Lerro, Hana Lee, David J. Graham, Mark Liberatore, Donna Rivera, Michael Leapman, Vikram Jairam, Michaela Ann Dinan, Cary Philip Gross, Henry Soo-Min Park
Journal: Journal of Clinical Oncology (2024)

11059 Background: Some opioid stewardship policies could negatively affect patients with cancer pain. However, patients with cancer are also at risk for opioid related harms, especially with persistent use. We assessed opioid prescribing trends in the context of cancer treatment and patient reported pain in a large health system in Connecticut. Methods: We conducted a retrospective cohort study of opioid-naïve adult patients with solid tumor malignancies diagnosed from 2016 through 2020 within the Yale New Haven Health System. We identified new (≥1 opioid prescription in 0-6 months following diagnosis) and additional (0-6 and 6-9 months) opioid prescriptions. The analysis evaluated all eligible patients as well as two clinical cohorts: patients treated surgically and patients with metastatic cancer. For patients with metastatic cancer and a documented pain score in the electronic health record flowsheet data, we further stratified by any (any score≥1) or no (all scores=0) pain in the 6 months since diagnosis and prior to first opioid, if given. For these patients, we noted therapeutic class of the first opioid. We used a logistic model adjusted for patient demographics to calculate predicted probability of opioid prescription and change over time. Results: A total of 10,868 patients met study criteria. Overall, we observed a decline in new opioid prescribing from 69.0% to 62.7% (p&lt;.001) (Table). Additional opioid use also declined from 23.4% to 20.2% (p=.02). In the surgery cohort, new opioid prescribing fell from 95.7% to 88.2% (p&lt;.001), while additional opioid use was stable over time (approximately 12%). For patients with metastatic cancer with any documented pain, new opioid prescribing was stable over time (approximately 56%). For those with documented pain scores=0, new opioid prescribing declined from 59.7% to 34.2% (p&lt;.001). In these patients, the class listed on the first opioid prescription was analgesia in 86.6% and cough in 13.4%. Conclusions: Overall, and in patients treated with oncological surgeries, our study in a single large US health system suggests a modest, gradual decline in opioid prescribing for patients with cancer over time. On the other hand, among patients with metastatic cancer, opioid prescribing remained stable for those with documented pain and declined steeply for those without documented pain. [Table: see text]
Implementation and preliminary efficacy of a risk stratification system +/- patient-reported outcomes monitoring for patients with hospital-diagnosed advanced lung cancer.
Authors: Emily Miller Ray, Amanda Gentry, Madeleine Ledenyi, Jennifer Elston Elston Lafata, Hanna Kelly Sanoff, Gita N Mody
Journal: Journal of Clinical Oncology (2024)

11095 Background: Risk stratification systems may improve quality of care for patients with advanced lung cancer (ALC) by identifying those at high risk of rehospitalization and directing them to supportive care. The purpose of this study was to evaluate the implementation and preliminary efficacy of a risk-based system, with/without electronic patient-reported outcome (ePRO) symptom monitoring, to trigger supportive care for patients with hospital-diagnosed ALC. Methods: In this single-site, non-randomized, pragmatic study, patients in an academic center with hospital-diagnosed ALC were stratified to low or high risk using an established tool. High-risk patients were referred to two-pronged supportive care: patient navigation and outpatient palliative care. Eligible patients were recruited for 3 months of ePRO symptom monitoring coupled with provider alerts. Healthcare utilization was assessed at 90 days post-discharge. Program feasibility and acceptability were assessed using percent of eligible supportive care referrals made and completed, enrollment rates in ePROs, ePRO completion, and notifications to providers of concerning symptoms. Preliminary efficacy was defined as percentage of concerning ePRO symptoms resulting in new clinical action and 90-day readmissions. Results: At the time of interim analysis, 49 patients had been assessed with 48/49 (98%) identified as high risk. Patients had a mean age of 66 years, and were non-Hispanic, 51% male, and 22% Black. Patient navigation referral (92%) and completion (88%) was high. Palliative care referral (89%) and completion (45%) was lower. 14/39 (36%) of eligible patients enrolled in ePRO symptom monitoring, with competing priorities or feeling overwhelmed as the primary reasons for non-participation. Patient-level ePRO completion ranged from 0-100% (mean 53%). Nearly all (97%) concerning symptoms were reported to the clinical team; 27% of these resulted in new clinical action. By 90 days, 16/37 (43%) had hospital readmissions. Conclusions: Patient navigation was feasible and acceptable in patients with hospital-diagnosed ALC. However, there are ongoing barriers to implementation of post-hospitalization ePRO symptom monitoring and palliative care. Additional evaluation is needed to understand the barriers and facilitators and to measure the impact of navigation on patient outcomes. Since nearly all patients met high-risk criteria, future programs will eliminate risk stratification and target all patients with hospital-diagnosed ALC. Clinical trial information: NCT05722847 . [Table: see text]
System-level variation in evidence-based multidisciplinary cancer care delivery.
Authors: Kelsey B. Montgomery, Joseph Cotler, Joshua S. Richman, Smita Bhatia, Kristy Kummerow Broman
Journal: Journal of Clinical Oncology (2024)

11064 Background: Widespread health system integration of hospitals continues to reshape the landscape of U.S. healthcare delivery. While complex cancer care has become centralized to high-volume centers, care for common cancers happens across the spectrum of hospital sizes, with known variation in receipt of evidence-based practice (EBP) based on system affiliation. Strategies are needed to evaluate system performance in order to identify system characteristics and processes that contribute to high-quality cancer care. Methods: Using a novel data linkage between the National Cancer Database and AHRQ Compendium of U.S. Health Systems, adult patients treated for breast, colon, melanoma, and thyroid cancers between 2010 and 2020 at Commission on Cancer (CoC) hospitals were identified. Systems were categorized based on number of CoC hospitals (small, 2-3; medium, 4-9; large, 10+). Eight EBP measures were developed using national multidisciplinary guidelines, and measure-specific cohorts were extracted to calculate system-level EBP performance and within-system variation using mixed effects multivariable logistic regression models. Systems were then ranked across all measures for performance and variation, and average rankings were compared by system size. Results: 3,052,453 patients with breast (60.0%), colon (17.0%), melanoma (14.0%), and thyroid (9.0%) cancers were treated at 866 CoC hospitals in 368 health systems. The 8-measure analytic cohort had 104 systems, most of which were small systems (n=74, 71.2%). Large systems (n=9, 8.7%) had worse average performance rankings compared to medium or small systems, though this was not statistically significant (p=0.1) (Table). A significant increase in within-system variation (as measured by average ranking of variability across EBP measures) was seen with increasing system size (p&lt;0.001). Conclusions: Significant variation in EBP performance for common cancers was noted based on health system size in this large, contemporary cohort, with greater within-system variation as system size increased. Future work will identify modifiable system characteristics associated with performance that could aid system leaders and policy makers to design, measure, and incentivize systems that employ effective cancer care delivery strategies. System rankings from 1 to 104 (best to worst), averaged over all measures; data presented as median (IQR). [Table: see text]
SPPADE symptom prevalence and severity in a diverse sample of patients living with metastatic cancers.
Authors: Deirdre R. Pachman, Kathryn Jean Ruddy, Veronica Grzegorczyk, Kurt Kroenke, Joan M. Griffin, Jennifer Ridgeway, Linda L. Chlan, Cindy Tofthagen, Konstantinos Leventakos, Jacob J. Strand, Jessica Austin, Ashley Wilder Smith, Sandra A. Mitchell, Jeph Herrin, Andrea L. Cheville
Journal: Journal of Clinical Oncology (2024)

11108 Background: Advances in cancer treatment have led to a growing population of patients living with metastatic cancer. Symptom burden for these patients is understudied. Our objective is to report the prevalence and severity of SPPADE symptoms (sleep disturbance, pain, physical function impairment, anxiety, depression, and low energy /fatigue) in a large cohort of patients with metastatic cancer. Methods: These data are drawn from the Enhanced, EHR-facilitated Cancer Symptom Control (E2C2) stepped wedge pragmatic trial evaluating a symptom management intervention for cancer patients (NCT03892967). This analysis was limited to those identified with metastatic disease using ICD- codes and a natural language processing algorithm prior to or within 30 days of their baseline symptom survey. Symptom severity was measured on a 0-10 scale with scores of 1-3 categorized as “mild”, 4-6 as “moderate”, and ≥7 as “severe.” A SPPADE composite score was calculated by summing six individual symptom scores and is an indicator of total symptom burden. We report descriptive statistics for each symptom by severity category. We also test for differences in SPPADE composite score by race, disability status, employment status, education and cancer type using Kruskal-Wallis tests. Results: 12,824 patients with metastatic disease completed a survey between March 2019 and January 2023. Discretized score distributions for the SPPADE symptoms are reported in the Table. The SPPADE composite mean score for the cohort was 17.6 (SD +/- 12.0). Significant differences were found in total symptom burden by sociodemographic and clinical characteristics ( p&lt;0.01): Higher total symptom burden (Mean [SD])was experienced by individuals who were American Indian/Alaska Native (AI/AN) (23.8[13.5]) or African American (AA) (20.5[14.7]), disabled (24.0[12.8]) or unemployed (21.1[13.0]), and had a high school education (20.0[13.3]) or less than high school education (18.5[12.4]). There were also statistically significant differences ( p&lt;0.01) in symptom burden across cancer types, with patients with metastatic lung cancer reporting the highest symptom burden (20.0[12.2]) and those with metastatic melanoma reporting the lowest (14.7[11.4]). Conclusions: SPPADE symptoms are common in patients with metastatic cancer, especially fatigue, sleep disturbance, and physical function impairment. Symptom burden is especially high in AI/AN, AA, disabled/unemployed, and less educated patients. Further research is needed to tailor symptom interventions among those living with metastatic disease. [Table: see text]
Impact of clinical response and AEs on health-related quality of life (HRQoL) in patients (pts) with R/R large B-cell lymphoma (LBCL): Pooled data from 4 lisocabtagene maraleucel (liso-cel) trials.
Authors: Patrick Connor Johnson, Jeremy S. Abramson, Ling Shi, Yeran Li, Laurie Eliason, Shien Guo, Fei Fei Liu, Leo I. Gordon
Journal: Journal of Clinical Oncology (2024)

11105 Background: Four liso-cel clinical trials in R/R LBCL (TRANSCEND NHL 001, PILOT, OUTREACH, and TRANSFORM) demonstrated a favorable clinical profile with high response rates (73%–80%) and positive changes in HRQoL after treatment. This analysis pooled data across 4 trials to assess the impact of clinical response and AEs on HRQoL. Methods: The EORTC QLQ-C30 and EQ-5D-5L were used to assess HRQoL repeatedly at prespecified time points up to Day 730. Six clinically relevant domains (EORTC QLQ-C30 global health status/quality of life [GHS/QoL], physical functioning, cognitive functioning, fatigue, pain, and the EQ-5D-5L visual analog scale [VAS]) were analyzed in liso-cel–treated pts pooled across trials with HRQoL scores at baseline and postbaseline visits. Linear mixed-effects regression models examined changes in HRQoL over time, with clinical response status and AEs as time-varying covariates, adjusting for relevant baseline and other time-varying factors. Trends in HRQoL change up to Day 730 over time were examined by cytokine release syndrome (CRS) and neurological events (NE) occurring ≤ 30 days after infusion. Results: The analysis included 368 and 372 pts for EORTC QLQ-C30 and EQ-5D-5L VAS, respectively. Achieving a clinical response (CR or PR) was associated with significant HRQoL improvement versus stable disease (SD) or PD in all 6 domains (Table). Meaningful improvement occurred ≤ 30 days after achieving CR or PR for all domains except cognitive functioning, where improvement occurred ≤ 90 days, and was sustained across remaining follow-up visits. CRS and NEs were associated with HRQoL worsening in selected domains; however, pts who experienced CRS or NEs ≤ 30 days after infusion recovered to levels of pts without the AE by Day 60 and maintained thereafter. Conclusions: Among liso-cel–treated pts with R/R LBCL, positive clinical response was associated with meaningful and sustained improvement in nearly all HRQoL domains. CRS and NEs may negatively impact certain HRQoL domains but are temporary. As liso-cel has demonstrated high response rates and a manageable safety profile across studies, these findings further support the pt-reported benefits of liso-cel for R/R LBCL. [Table: see text]
Correlation of stress, depression, sleep, and pain with race and body mass index (BMI): Secondary analysis from Alliance A011502.
Authors: Shipra Gandhi, Karla V. Ballman, Michelle D. Holmes, Kala Visvanathan, Banu Symington, Margaret Carvan, Carol Matyka, Anna Weiss, Eric P. Winer, Wajeeha Razaq, Lisa A. Carey, Ann H. Partridge, Wendy Y. Chen
Journal: Journal of Clinical Oncology (2024)

e23171 Background: A011502 is a phase 3 trial that randomized high-risk nonmetastatic breast cancer (BC) patients (pts) to aspirin 300 mg daily vs. placebo. Obesity and Black race have been shown to be associated with worse clinical outcomes. We studied the association of stress, depression, sleep and pain with each other, and with BMI and race. Methods: At baseline, 2735, 2610, 2720, and 2422 pts completed Perceived Stress Scale (PSS), Center for Epidemiologic Studies Depression Scale Revised (CESD-R), Brief Pain Inventory (BPI), and Pittsburgh Sleep Quality Index (PSQI) respectively. Stress was categorized with PSS scores: low (0-13), moderate (14-26) or high (27-40). Depression was categorized with CESD-R scores: no depression (0-15) or depression (≥16). Pain was categorized with BPI scores: none/mild (0-3) or moderate/severe (≥4). Sleep quality was categorized with PSQI scores: good (0-5) or poor ( &gt; 5). Associations of measures by race and BMI were analyzed using chi-square test. Results: There was a statistically significant association among stress, depression, pain, and sleep quality (p &lt; 0.01 for all). Compared to pts with BMI &lt; 25, overweight and obese women reported higher stress (2.9%, 2.3% vs. 1.7%, p = 0.04), depression (13.4%, 18% vs. 9.6%, p &lt; 0.01), moderate/severe pain (16.5%, 20.3% vs. 12%, p &lt; 0.01), and poor sleep (64.9%, 71.5% vs. 60.4%, p &lt; 0.01). Black women reported more moderate/severe pain compared to White women or other races (32.9% vs. 14.2% vs. 27.8%, p &lt; 0.01). There was no association of other symptoms with race (Table 1). Conclusions: Obesity was associated with higher stress, depression, poor sleep and pain among BC pts from A011502. Black women reported higher pain compared to other races. Future studies are warranted that determine causal associations, how symptoms may relate to outcome disparities, and develop approaches to address them. U10CA180821, U10CA180882, UG1CA233196; https://acknowledgments.alliancefound.org . Clinical trial information: NCT02927249 . [Table: see text]
An analysis of the trends and distribution of political contributions from hematologists and oncologists in the United States.
Authors: Shanawar Ali Waris, Nanda Siva, Imtisaal Waris, Adnan Saifuddin, Sriram Dasu, Salah Ud Din Safi
Journal: Journal of Clinical Oncology (2024)

e23041 Background: In today's increasingly tumultuous political landscape, understanding how healthcare providers are engaging the system to contribute to shaping the future of healthcare policy has become increasingly important. Policy can directly influence funding priorities, research agendas, and regulations for providers. This cross-sectional study aims to assess political contributions made by hematologists and oncologists across the United States from 2009-2022. Methods: Political donations to the U.S. Presidential, Senate, and House of Representatives campaigns made by hematologists and oncologists between 2009-2022 were collected from the Federal Election Commission database. Keywords used in the occupation search query were “oncologist”, “hematologist”, “oncology”, and “hematology”; the raw data was filtered to remove non-physicians. Each individual contribution was addressed to a recipient committee, which were characterized as “Democratic”, “Republican”, or “Independent”. Results: From 2009 to 2022, a total of 2889 contributions were made by hematologists and oncologists to campaigns for presidential and national legislative campaigns grossing a total of 1,324,397 with a mean donation value of $458 per contribution. Of campaign contributions, 68% ( $905,388), 31% ($405,257), and 1% ($13,751) went to democratic, republican, and independent campaigns respectively. The total number of contributions increased from 77 totaling a sum of $48,902 in 2009 to 203 totaling a sum of $107,281 in 2022. Republicans experienced an increase in total dollar amount of contributions of 9.42% from 2009 to 2022. The top five states with the highest contributions in dollar amount were California, Texas, Maryland, Florida, and Georgia, in descending order. Conclusions: The total political contribution amount made by hematologists and oncologists in the United States has increased from 2009 to 2022. Further investigation of how physician contributions influence the development and implementation of healthcare policies is imperative.
Influence of sociodemographic factors on time to diagnosis and treatment among members of a large national payor diagnosed with lung cancer.
Authors: Shirisha Reddy, Brooke Byrd, Kelly Craig, Amanda Zaleski, Cliff Rutter, Shannon McKeever, Meghana Bhandari, Karla Dalton, Leah Altieri-Alger, Dorothea J. Verbrugge, Elisea Avalos-Reyes, Kjel Andrew Johnson, Rogelio Brito
Journal: Journal of Clinical Oncology (2024)

e23048 Background: Diagnostic and treatment delays may be associated with later stage lung cancer diagnosis. This study explores the time from lung cancer screening to biopsy and biopsy to treatment in members of a national health plan diagnosed with lung cancer. Methods: De-identified administrative records of Medicare, Medicaid and Commercial fully-insured (C-FI) members with a claim for lung cancer between January 2020 and December 2022 were retrospectively analyzed. Poisson regression modeling determined duration (days) from screening to biopsy and biopsy to treatment initiation by insurance type group controlling for covariates. Between-group differences in duration was estimated by exponentiating the model estimate and converting to a percentage change, which was then applied to the mean days to event. Time-to-event modelling was conducted with Cox Proportional and Aelen’s Additive Hazard models. P&lt; 0.05 was considered significant. Results: 8,221 members (C-FI: 402; Medicare: 7,103; Medicaid: 716) with a diagnosis of lung cancer were evaluated. Mean duration between screening and biopsy was 34.3 days (95% confidence interval [CI]: 32.8-35.8). Compared to C-FI members, Medicaid and Medicare members experienced shorter duration between screening to biopsy by -14.0 days (95% CI: 13.1-14.9) and -18.9 days (95% CI: 18.2-19.5), respectively (both P&lt; 0.0001). Gender, language, age, and race were associated with time to biopsy (all P&lt; 0.001). Mean duration between biopsy and treatment was 37.9 days (95% CI: 36.8-39.0). Compared to C-FI members, Medicare and Medicaid members experienced a longer duration between biopsy to treatment by +14.6 days (95% CI: 12.1-17.3) and +22.5 days (95% CI: 19.4-25.8), respectively (both P&lt; 0.0001). Compared to C-FI members, Medicaid members had a higher risk of not receiving treatment (Hazard ratio [HR] = 0.831; 95% CI: 0.735-0.939; P= 0.003). Among the total sample, males were more likely to receive treatment at any time compared to females (HR = 1.067; 95% CI: 1.021-1.114; P= 0.0035). Conclusions: This real-world evaluation suggests that insurance type is associated with the timeline of screening to biopsy and biopsy to treatment initiation. Medicaid and Medicare members had a shorter time from screening to biopsy compared to C-FI; however, a longer duration from biopsy to treatment initiation was experienced. Future studies will explore if these differences translate to variations in health outcomes and identify potential interventions that aim to improve time from biopsy to treatment initiation.
Factors linked to patient rehabilitation disposition following surgical treatment of bone-related complications.
Authors: Jagger Corabi, Vivian Yan, Atrayee B. Mallick, Adam F. Binder
Journal: Journal of Clinical Oncology (2024)

e23061 Background: Cancer in the skeletal system, whether primary or metastatic, can cause fractures or impending fractures needing stabilization. Patients with pathologic fractures or impending fractures needing prophylactic fixation have lower home discharge rates than non-malignant hip fracture cases, a recognized quality metric. We initiated a single-center retrospective study to identify modifiable risk factors for improving home discharge rates in this population. Methods: We reviewed orthopedic surgery patients at Thomas Jefferson University Hospital (TJUH) from July 2020 to April 2023. We assessed demographics, living situation, admission-to-surgery time, surgery-to-physical therapy time, in-hospital complications, pathological fracture site, and weight-bearing status. Patients were stratified into discharge groups: home, subacute rehabilitation, and acute rehabilitation. Differences in rehabilitation facility versus home discharges were analyzed using pairwise two-sample t-tests and Fisher exact tests. Results: In this study, 102 cancer patients underwent orthopedic intervention at TJUH. The cohort comprised 57 women (55.9%), 67 non-Hispanic white individuals (63.7%), with median age of 66.6 (52.4-80.8). Living alone increased the likelihood of discharge to an acute rehabilitation facility compared to home (13 vs. 5, p&lt;.001). Lower median age correlated with home discharge compared to subacute and acute discharge (age 62.4 vs. 74.7, p&lt;0.001; 62.4 vs. 66.9, p&lt;0.05). Higher in-hospital complications, like sepsis, were associated with acute rehabilitation discharge versus home (24 vs. 17, p&lt;.05). Conclusions: These results link living alone, older age, and in-hospital complications to rehabilitation facility discharge. No modifiable risk factors for home discharge were identified. This study reinforces the importance of caregiver support for patient outcomes and high-quality care. In the future, we intend to investigate if the in-hospital complications were avoidable and, thus, modifiable. A larger patient cohort may be required to reveal potential areas for improvement. [Table: see text]