tbuckley/cabot-search huggingface dataset:
Identifying modifiable risk factors to improve immigrant breast cancer screening in the United States.
Authors: Patricia Mae Garcia Santos, Justin Michael Barnes, Lillian A Boe, Kanan Shah, Robin Yabroff, Fumiko Chino
Journal: Journal of Clinical Oncology (2024)

1530 Background: Despite marked reductions in breast cancer mortality since 1990, recent data suggest that progress has slowed—owing in part to plateaus in breast cancer screening in underserved populations. Historically low rates of screening coupled with rising breast cancer incidence make immigrants an important population for targeted intervention. Herein, we (1) compare contemporary rates of breast cancer screening among immigrants versus US natives; and (2) identify modifiable risk factors to inform the development of interventions to improve screening among immigrants in the United States. Methods: Using data from the 2019 and 2021 National Health Interview Surveys, screening eligible female participants (ages 40-79 years old) were identified, then classified by immigrant status as defined by nativity (US native vs. foreign-born). Primary outcome was receipt of screening mammogram in the last two years. Logistic regression models examined associations between immigrant status and mammography, with and without adjustments for age, metropolitan residence, overall health status, and survey year. Sequential analysis was then used to assess the degree to which modifiable social risk factors influence the magnitude of the association between immigrant status and mammography. Results: Of 20,090 female participants included in the study, 20% were immigrants. Compared to US natives, immigrants were less likely to have received a mammogram in the last two years (67% vs. 72%, aOR [95%CI], 0.87 [0.78-0.96], p=0.006)—an effect that was most pronounced among immigrant noncitizens (57%; 0.55 [0.47-0.64], p&lt;0.001) but reversed among immigrants with US citizenship (74%; 1.14 [1.01-1.29], p=0.03). Of the factors assessed, having a usual source of care (5.73 [4.77-6.87]) or insurance (4.60 [3.74-5.67]) was associated with the greatest odds of biennial mammography, followed by educational attainment (1.38 [1.19-1.60]) and employment (1.19 [1.09-1.30]; all p&lt;0.001). While having a usual source of care or employment attenuated—but did not eliminate—the association between immigrant status and mammography (0.87 [0.78-0.96], p=0.01 and 0.89 [0.80-0.99], p=0.03, respectively), this finding was not observed upon inclusion of insurance status or education in sequential models (0.97 [0.87-1.09], p=0.6 and 1.09 [0.96-1.21], p=0.13, respectively). With respect to insurance type, Medicare Advantage (4.60 [3.74-5.67]) conferred the largest benefit, followed by private insurance (4.54 [4.00-5.26]), Medicaid (2.63 [2.20-3.14]), and Medicare (4.39 [3.53-5.46]; all p&lt;0.001). Conclusions: Breast cancer screening remains low in noncitizen immigrant populations. Targeted interventions to improve access to health insurance coverage and primary care for noncitizens may be most effective for improving rates of screening mammography among immigrants and thus warrant further investigation.
Updated estimates of eligibility and response: Immune checkpoint inhibitors.
Authors: Vinay Prasad, Alyson Haslam, Timothee Olivier
Journal: Journal of Clinical Oncology (2024)

e14613 Background: Immune checkpoint inhibitors (ICIs) have notably changed the landscape of systemic treatment of advanced and metastatic cancers in the last decade. We previously estimated the eligibility for and responses to ICIs, but since then, there have been multiple approvals for additional indications. As such, we have updated these estimates to include all approvals, as of December 2023. Methods: For eligibility, we used death data from the American Cancer Society’s Cancer Facts and Figures. Deaths was used as a stand-in for eligibility because these therapies are often given in later lines. Data from the peer-reviewed literature was used to further refine specific tumor type estimates (e.g., the percentage of lung cancers that are non-small cell and small cell lung cancer). For each tumor type, we multiplied the response rates reported in the FDA’s package insert by the number of deaths for each respective tumor type. When multiple drugs were approved for the same indication, we used the highest response rate. Results: Eleven ICI drugs were approved for 88 different indication approvals in the advanced/metastatic setting between 2015 and 2023. These approvals were for 20 general tumor types. The estimated eligibility for ICIs increased from 1.54% in 2011 to 55.47% in 2023. The tumor types with the highest eligibility in 2023 were non-small cell lung cancer with PDL1 status of 50% (13.28%) or less and PDL1 status &gt;50% (4.42%), solid tumors TMB-h (6.81%), and hepatocellular (4.82%). The estimated response to ICIs increased from 0.14% in 2011 to 19.60% in 2023. The tumor types with the highest contribution to response estimates in 2023 were non-small cell lung cancer with PDL1 status of 50% (4.78%) or less and PDL1 status &gt;50% (1.99%), solid tumors TMB-h (2.72%), and renal cell carcinoma (1.95%). Conclusions: We find that the estimated eligibility for and response to ICIs has increased since their introduction in 2011. Our estimates are an upper bound since many people are not eligible due to contraindications or healthcare coverage. Both the response and eligibility were driven by certain tumor types, including non-small cell lung cancer (either PDL1 high or PDL1 low). Patients with these types of tumors made up about one-third of the estimated response and eligibility. Solid tumors TMB-h, hepatocellular and renal cell carcinoma were other tumors with high eligibility and response, but other tumor types had low eligibility and response. While many patients have benefited from ICIs, half of patients with advanced or metastatic cancers are either not eligible or likely do not respond. [Table: see text]
Integrating 4 Methods (In4M) to evaluate physical function in patients with cancer: Results of a comprehensive digital health study.
Authors: Gita Thanarajasingam, Amylou C. Dueck, Vishal Bhatnagar, Abbie Brown, Elizabeth Jane Cathcart-Rake, Matthew Diamond, Louis Faust, Mallorie Fiero, Scott F. Huntington, Molly Jeffery, Lee Jones, Jonas Paludo, Bradford Power, Joseph S. Ross, Kathryn Jean Ruddy, Sarah Schellhorn, Michelle Tarver, William Allen Wood, Cary Philip Gross, Paul Gustav Kluetz
Journal: Journal of Clinical Oncology (2024)

1564 Background: Physical function (PF) is a core outcome in cancer trials that can inform treatment tolerability. PF can be assessed across modalities including by patient (pt) report, clinician (clin) report, performance tests and digital sensors. The optimal approach for PF measurement has not been defined. Methods: In4M is a prospective observational study evaluating PF in pts initiating chemotherapy for breast cancer or lymphoma followed over 9 months. We used an electronic platform (Hugo) to aggregate serially assessed pt-reported PF, clin- and pt-reported ECOG performance status (PS), 6-minute walk test (6MWT) and wearable (Fitbit) data. We evaluated feasibility in all pts; associations among PF measures and the ability of PF measures to detect change were evaluated in pts with both baseline (BL) and 3-month (3M) data. We used Pearson correlations to assess the relationship of average daily steps with measures of PF. To assess change, we compared each PF measure from BL to 3M using a 2-sided α=.05 paired t-test. Results: Of the208 pts enrolled, 193 (93%) and 159 (76%) completed surveys, and 121 (58%) and 124 (60%) provided wearable data (evaluable: ≥1 day data) at BL and 3M, respectively. When requiring a stringent BL with 4+ days of data with ≥1 weekend day to be evaluable, 88 (42%) and 120 (58%) provided wearable data at BL and 3M. At both BL and 3M, pt-reported PF was generally more highly correlated with wearable-derived daily steps than clin-reported PF and 6MWT were (Table). Significant declines in PF were observed for pt- and clin-reported PF (all p&lt;0.05), but not other modalities. Conclusions: Longitudinalassessment of multi-modal PF data including pragmatic wearable data collection was feasible in pts receiving chemotherapy. Pt-reported PF was the only modality that was both correlated with step count and able to detect change. Additional wearable metrics, correlations among PF measurements and outcomes, and clinically meaningful change scores will be reported. Optimal PF measurement may improve future reporting of treatment tolerability. Clinical trial information: NCT05214144 . [Table: see text]
Immune checkpoint inhibitor (ICI) rechallenge after immune-related adverse events (irAE) requiring hospitalization: A single-center 10-year experience.
Authors: Chia-Yun Wu, Leyre Zubiri, Sherin Juliet Rouhani, Ross D. Merkin, Allison Holt, Ayo Samuel Falade, Kelley Grealish, Nora Hathaway, Kerry Lynn Reynolds
Journal: Journal of Clinical Oncology (2024)

e14609 Background: ICI rechallenge after irAE has become a significant clinical dilemma, with irAE recurrence rates of 30-40% after rechallenge. Here we examine factors influencing ICI rechallenge rates across a 10-year period at the Massachusetts General Hospital (MGH), where the Severe Immunotherapy Complications service is available to provide multidisciplinary irAE expertise. Methods: We included patients admitted to MGH for an irAE from August 2011 to July 2023. We collected baseline demographics, ICI regimens, and irAE features. The choice of ICI used at rechallenge was grouped into 3 categories: 1) restarting an ICI within the same class, 2) switching classes (CTLA-4 to PD-(L)1 or vice versa), or 3) de-escalating from combination to monotherapy. Chi-square and Mann-Whitney U tests were applied to descriptive statistics. Results: Among 5882 patients treated with ICI, 671 (11.4%) patients were admitted for irAE. The median age was 67.6 (IQR, 59-74.9) years and 58% were male. Initial ICI regimens consisted of anti-PD-(L)1 (64.8%), anti-CTLA4 (10.9%), and ICI combinations (24.3%). 174 of 671 patients (25.9%) were rechallenged after an irAE requiring hospitalization. Rechallenge was common after rheumatologic, endocrine, dermatologic irAE and GI irAE, but rare after cardiac, neurologic, or pulmonary irAE (Table 1). The median time to rechallenge was 25 days (IQR 18-91) after endocrine irAE and 72 days (IQR 40-209) after non-endocrine irAE (p&lt;0.001). Rechallenge was more common in melanoma (35%, p&lt;0.001), and less common in lung (13.6%, p&lt;0.001) and GU cancers (10%, p=0.003). Rechallenge rates were significantly higher in patients initially on combination therapy (39.6%) versus PD-(L)1 monotherapy (15.5%), p&lt;0.001. Of those rechallenged, 43.2% initially on combination therapy were de-escalated to monotherapy and 53% were restarted within the same class. Amongst the PD-(L)1 monotherapy group, 88.4% were restarted within the same class and 11.6% switched classes. Conclusions: Here we examine practice patterns at a large academic center, where 25.9% of patients with irAE requiring hospitalization were rechallenged. Rechallenge was more prevalent in patients with melanoma or on ICI combination therapy, whereas it was less frequent following cardiac, neurologic, or pulmonary irAE. Under adequate risk-benefit evaluation, close monitoring, and multidisciplinary care, ICI rechallenge can be considered. [Table: see text]
Ensuring precision medicine for veterans with lung cancer: A randomized clinical trial.
Authors: Mikalah Thomas, Hector Gonzalez, Madhuri Agrawal, Millie Das, Manali I. Patel
Journal: Journal of Clinical Oncology (2024)

1501 Background: National guidelines recommend molecular testing for patients with non-small cell lung cancer, yet this is not routinely completed in practice. In prior work, we identified barriers to testing in the Veterans Affairs. First, physicians are unaware if and when testing has occurred. Second, patients are unaware of testing and the implications on treatment and clinical outcomes. In response, in collaboration with a Veteran and Caregiver Advisory Board, we created a multilevel intervention led by a peer volunteer who: 1) provides tailored education of molecular testing for 1 month for Veterans newly diagnosed with lung cancer and, 2) alerts clinicians via secure messaging if tumor samples have not been tested. We conducted this randomized clinical trial to assess whether the intervention improves patient knowledge of molecular testing and patient activation and increases receipt of molecular genomic testing compared with usual care. Methods: All veterans &gt;18 years old with a new diagnosis of any stage non-small cell lung cancer were eligible. Exclusions included inability to consent. All participants completed baseline assessments at randomization and at 1-month follow-up comprised of a 3-question validated precision medicine knowledge questionnaire and a 13-question validated patient activation measure. Genomic testing was assessed by chart review at 6-months followup. We used regression models to assess differences in mean knowledge and activation scores over time between groups and compared rates of genomic testing. Results: 75 Veterans were screened with 46 eligible. All 46 consented to participate, with 23 in each group. All were male (100%), had mean age of 76.3+/-5.54 years; 31 (67.4%) were Latinx; 2 (4.4%) Asian; 11 (23.9%) Black; 1 (2.2%) Native Hawaiian; 32 (69.6%) White; 32 (69.6%) had Stage 4 disease. At 1 month follow-up mean knowledge scores increased over time in the intervention group and remained stable in the control group (mean score 2.30 +/- 0.97 versus 1.16 +/- 1.15, p=0.014). At 1-month follow-up, patient activation increased for the intervention group more than the control group (46.7 +/- 11.3 versus 37.6 +/- 9.26, p=0.002). There were no significant differences in tumor testing between groups (intervention: 95.6% versus control: 86.9%, p=0.62). Conclusions: A volunteer led effort improved patient education regarding precision medicine and patient activation among Veterans as compared with usual care alone. Interventions that include volunteers and other support can enhance care and clinical outcomes among veterans with lung cancer. Clinical trial information: NCT05795959 .
Clinical impact and financial feasibility of remote oncology pharmacists' roles in community oncology practices.
Authors: Andrea Roman, Judy Cho, Juna Jovani, Caroline Farag, Melissa Carroll, Hilary Conkling, Natalie Greisl, Brittney Hale, Daniel Kendzierski, Meredith Keisler, Beth Koselke, Shannon Hough
Journal: Journal of Clinical Oncology (2024)

1545 Background: The clinical and financial impact of oncology-trained pharmacists in the community oncology setting has not been well documented. The US Oncology Network has introduced a novel remote oncology pharmacist model which provides clinical services to oncology community practices to alleviate the burden on oncologists, enhance patient care, and improve workflows. Methods: Oncology-trained pharmacists remotely reviewed chemotherapy regimens across 12 community oncology practices. Pharmacists identified opportunities to modify therapy based on clinical criteria, waste reduction, and/or financial stewardship. These modifications were discussed with the treatment team or implemented in accordance with practice-approved policies. Clinical and financial metrics were tracked to assess the overall impact of the pharmacist interventions and provider time saved. Results: From January 1, 2023, through December 31, 2023, 27,938 reviews were documented for 19,962 patients. Among these reviews, the majority (14,572, 73%) required modification by the pharmacist, and many (3,005, 21%) were deemed clinically significant by the intervening pharmacist. The most common clinically significant interventions included changes to anticancer drug doses (1155, 38%), modifications to supportive care (742, 25%) and recommendations for additional monitoring (426, 14%). Across 12 practices, 63 drug-related workflow policies were implemented allowing pharmacists to autonomously auto-substitute products, order laboratory tests and adjust chemotherapy doses. These policies saved over 600 hours of physician time. Pharmacist involvement resulted in medication-related margin improvements totaling $9.3M. Practices also experienced a $4.3M reduction in the total cost of care in medication expenses. The cost of the pharmacists during this period was $1.4M, equating to a 560% return on investment compared to margin improvement. Conclusions: Community oncology practices operate within a resource-constrained model with limited access to oncology pharmacists. As invaluable members of the care team, pharmacists identified opportunities to significantly enhance clinical care by focusing on medication safety, dosing, and regimen optimization, while demonstrating a tremendous financial impact on small-scale budgets. Oncology-trained pharmacists play a vital role in alleviating care burden of the clinical team by collaboratively developing practice-approved policies and reviewing clinical orders in a high-risk patient population.
Toxicity of weight-based vs. flat dosing for immune checkpoint inhibitors in patients with low weight: Retrospective analysis from a tertiary care center.
Authors: Hussein Hamad, Ravi Kumar Kyasaram, Ankit Mangla
Journal: Journal of Clinical Oncology (2024)

e14616 Background: Immune checkpoint inhibitors (ICI) have come to the forefront of cancer therapy. Barring Ipilimumab, all other ICIs are dosed at flat doses for ease of administration. Pharmacokinetic studies have shown a wide range of peak and trough concentrations for flat doses. However, for underweight patients (&lt;50 Kg), when one looks at weight-based dosing, it may seem that flat dose may deliver excessive amounts of the drug within a short period of time, which in turn may cause an immune-related adverse event (irAE). We conducted a retrospective study comparing the toxicities and outcomes of weight based and flat doses in underweight patients treated with ICI. Methods: This is a retrospective study of patients receiving ICI for any cancer-related indication. Patients receiving chemotherapy with pembrolizumab, nivolumab and/or ipilimumab were included. Patients on other ICI were excluded. All grade toxicities were recorded, and Odds ratio (OR) was calculated using the Z-test. Results: 313 patients were included where 255 (81.5%) were females, median age 66 years (range 19-93), and 225 (72%) were White. Lung cancer was the most common histology (n-170, 54%) followed by H&amp;N (n-34, 11%) and GI cancers (n- 27, 9%). The median weight was 47 Kgs (range: 31-50). 252 patients (80.5%) received flat dose ICI and 61 patients (19.5%) received weight-based ICI, most of whom (n-45, 74%) received prior to 2018. Median ICI cycles was 4 (2-9) vs. 5 (3-10). Single agent PDL-1 inhibitor was prescribed to 205 patients (65%) of which 120 received pembrolizumab (59%) and 85 received nivolumab (41%), and 89 patients (28%) received ICI in combination with chemo or targeted therapy. 94 patients (30%) experienced all grade toxicities. Thyroid dysfunction (n-47, 15%) and colitis (n-24, 8%) were the most common. There was a non-significant trend towards lower toxicity in weight-based dosing: 13 (21.3%) vs. 81 (32.1%), OR =0.57, 95% CI (0.29 - 1.11) p =0.10, and a trend toward less hospitalization or need for treatment for iRAE: 8 (13.1%) vs. 55 (21.8%), OR =0.54, 95% CI (0.24 - 1.20) p=0.13. Significantly higher toxicity was recorded when chemotherapy-ICI or TT-ICI combinations: 56 (24.8%) vs. 38 (43.7%) OR = 0.42, 95% CI (0.25 - 0.71) p= 0.001. There was no difference in death or needing hospice care rates: 43 (70.5%) vs 169 (67.1%), OR= 1.17 (95% CI, 0.64 - 2.16) p= 0.61. Conclusions: Compared to standard flat dosing, weight-based dosing of ICI was associated with a trend towards lower iRAE in patients &lt; 50 Kgs without a difference in survival. These results urge the oncology community to consider the potential financial toxicity savings if weight-based dosing of ICI is adopted more broadly in underweight patients without negatively impacting outcomes, large scale and prospective studies are needed to support this hypothesis.
Artificial intelligence (AI) content detection in ASCO scientific abstracts from 2021 to 2023.
Authors: Frederick Matthew Howard, Anran Li, Mark Riffon, Elizabeth Garrett-Mayer, Alexander T. Pearson
Journal: Journal of Clinical Oncology (2024)

1565 Background: Generative AI models such as OpenAI’s ChatGPT have been broadly utilized throughout the medical literature. Previous studies have found that AI can generate scientific abstracts which can be difficult to distinguish from the work of human authors. There is a pressing need to characterize utilization of AI in scientific writing to guide policy. Methods: In collaboration with ASCO's Center for Research and Analytics, we extracted text from all scientific abstracts submitted to ASCO 2021 – 2023 Annual Meetings. Likelihood of AI content was evaluated by four AI detectors: GPTZero, Originality.ai (OGAI), Sapling, and Kashyap's AI Content Detector (AICD). Each detector produces a numeric likelihood of AI content. Predictions were dichotomized for uniform analysis across detectors: those in the top 5% for a given detector were considered as having high likelihood of AI content. Logistic regression was used to compute odds ratio (OR) for AI-generated content with respect to submission year and abstract characteristics. Predictions were also assessed for 10 human-written abstracts as negative controls, and 10 produced by OpenAI’s GPT-3 and GPT-4 models as positive controls. Results: 15,553 abstracts met inclusion criteria. 5,179 (33%) were published online only, and 5,327 (34%) referenced registered clinical trials. Across all detectors, abstracts submitted in 2023 were significantly more likely to contain AI content than those in 2021 (OR range 1.3 - 1.7). In abstracts from 2023, AI content score was associated with online only publication, lack of clinical trial number, and abstract track (Table). None of the 10 negative control human written abstracts were identified as AI generated, whereas 100%, 95%, 90%, and 30% of the GPT-3/4 generated abstracts were classified as AI generated by Sapling, GPTZero, OGAI, and AICD respectively using the 5% threshold. Additional results will be presented. Conclusions: AI content detectors uniformly suggest a higher likelihood of AI content generation for abstracts submitted in 2023. Predicted AI content is associated with triage of abstracts to online only presentation, suggesting predicted AI content is associated with lower perceived abstract quality. Further work is needed to understand the accuracy of AI detectors and utility in the abstract review process. [Table: see text]