tbuckley/cabot-search huggingface dataset:
Influence of health insurance type on time to breast cancer diagnosis and treatment among members of a large national payor.
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)

e23049 Background: Delays in breast cancer diagnosis and treatment can decrease early screening benefits. This study investigates the relationship between health insurance type and time from cancer screening to biopsy and biopsy to treatment initiation in members of a national health plan diagnosed with breast cancer. Methods: De-identified administrative records of Medicare, Medicaid and Commercial fully insured (C-FI) members with a claim for breast 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 were estimated by exponentiating the model estimate and converting to a percentage change, which was then applied to the mean days to event. P&lt; 0.05 was considered significant. Results: 29,731 members (C-FI: 5,256; Medicare: 22,304; Medicaid: 2,171) with a diagnosis of breast cancer were evaluated. Mean duration from screening to biopsy was 21.5 days (95% confidence interval [CI]: 20.9-22.0). Insurance type was associated with time from screening to biopsy. Compared to C-FI members, Medicaid members experienced a longer duration between screening and biopsy by +12.6 days (95% CI: 11.7-13.6; P&lt; 0.0001). Compared to C-FI members, Medicare members received biopsies 3.4 days sooner (95% CI: 3.0-3.8; P&lt; 0.0001). Mean duration from biopsy to treatment was 35.4 days (95% CI: 34.9-35.9) with similar differences by insurance type. Compared to C-Fl members, Medicaid members experienced a longer duration between biopsy and treatment by +7.9 days (95% CI: 6.9-9.0; P&lt; 0.0001). Compared to C-FI, Medicare members received treatment 3.6 days sooner (95% CI: 3.0-4.1; P&lt; 0.0001). Conclusions: Health insurance type appears to impact time from breast cancer screening to biopsy and treatment initiation. Medicaid members may experience longer duration for both time from screening to biopsy and biopsy to treatment. Future studies will explore if these variations translate to clinically meaningful health outcomes and identify opportunities to provide additional support for individuals experiencing breast cancer.
Administrative burden of establishing health care coverage for the uninsured and its impact on timely access to care.
Authors: Laura Wang, Arthur S Hong, Aman Narayan, Navid Sadeghi, Ethan A Halm
Journal: Journal of Clinical Oncology (2024)

11050 Background: Although safety net coverage programs like Medicaid exist to fund health care for low-income patients, the administrative burden of the lengthy application limits uptake by eligible individuals. Therefore, many patients do not attempt to enroll until they become ill, which is common among uninsured adults diagnosed with cancer. The literature reports worse cancer outcomes for those with Medicaid, but reasons for this are unclear. The delays in enrollment for patients with uncertain coverage at the time of diagnosis – those in limbo – are understudied and may explain some of this persisting disparity. We estimated the patient and health system burdens for those with uncertain coverage status at the time of cancer diagnosis at Parkland Health, the main provider of cancer treatment for the uninsured in Dallas, Texas. Methods: We assembled the electronic health record financial encounter data of patients with an incident cancer diagnosis in the Parkland tumor registry, diagnosed from 2010 – 2022. We defined patients as being “in limbo” if they had self-pay, pending, or missing insurance plans at the date of diagnosis. We also included patients whose coverage verification date occurred after diagnosis date, since coverage programs can apply retroactively for 90 days. We used plan verification dates to identify when limbo status resolved. We used coarsened exact matching to balance across age, race, Spanish-language preference, Charlson, and screenable cancer type, then multivariate regression to compare patients that were in limbo to those that had established coverage before cancer diagnosis. Results: We identified 17,468 adults newly diagnosed with cancer, 80% of whom were &lt; age 65, 55% female, 73% Hispanic and/or Black, and 30% Spanish-language preferring. The most common cancer types were GI/colorectal (19%), breast (17%), and lung (9%); 23% were advanced stage at diagnosis and 13% died within 180 days of diagnosis. 52.1% were already enrolled in Medicaid/charity care, but one-third (35%) were in limbo at diagnosis, which lasted for a median 31 days (IQR 13 – 126). Over half (55%) of patients in limbo resolved to Medicaid or charity care. Patients who experienced limbo had a median of 596 financial account notes in the first year after diagnosis, 121 more than the comparison group (95% CI 86.7 - 156.1) and began treatment 10 days later (95% CI 7.7 - 12.7). They also had a median of 1 ED visit in the year after diagnosis, 0.2 more than patients never in limbo (95% CI 0.11 - 0.26). Conclusions: The administrative burden of enrolling into coverage programs for the uninsured may impose direct and indirect costs on patients and safety-net health systems and may contribute to worse cancer care outcomes. A more comprehensive accounting of the effects of administrative burdens might suggest ways to redesign coverage enrollment for the uninsured to improve care and reduce costs.
Impact of cancer treatment in patients with inflammatory bowel disease: A systematic review and meta analysis.
Authors: Vaibhavi Mukhtiar, Mythili Menon, Ronit Juthani, Kala Seetharaman
Journal: Journal of Clinical Oncology (2024)

e23084 Background: The association between cancer treatments and impact of inflammatory bowel diseases (IBD) remains uncertain. Given the growing prevalence of IBD globally, it is crucial to understand the impact of various cancer treatments in this patient population to make informed decisions and optimize outcomes. Thus, the objective of our systematic review is to assess how cancer treatments impact the activity of underlying IBD. Methods: We performed a systematic review of the literature on cancer therapy in patients with pre-existing IBD. Various databases like PubMed, Cochrane, Embase and Google Scholar were searched for studies reporting effects of cancer treatment in patients with IBD, till February 1, 2024. Studies without relevant data were excluded. The outcomes studied were the flares of IBD following cancer treatment and initiation of systemic steroids or biologics for management of IBD flares. Results: In total, 36 studies were included which comprised 1,443 patients with IBD who received cancer treatment. The overall occurrence of IBD flares in patients with IBD receiving cancer treatment was 28% (CI 22.9%-33.8%, I2= 68%) out of which 35.9% (CI 27.5% - 45.3%, I2= 40) had received immune checkpoint inhibitor therapy. The flares resulted in the utilization of systemic steroids and biologics in 27% and 10% respectively. Conclusions: While the data suggests a high proportion of patients with IBD experience flares during cancer treatment, all of the reported episodes were manageable with steroids and/or biologics. However, the population studied only included 1443 patients, and larger population studies are required to optimize individual outcomes, and to explore methods to minimize severity and frequency of flares, when possible.
Examining the financial landscape of cancer: An analysis of debt and bankruptcy among patients in Massachusetts (2010-2019).
Authors: Nishant Uppal, Jorge Gomez-Mayorga, Aaron Fleishman, Ashley L. O’Donoghue, Anastasia Bogdanovski, Katharine Esselen, Benjamin James
Journal: Journal of Clinical Oncology (2024)

11032 Background: Financial toxicity is commonly reported by patients following a cancer diagnosis. Prior patient surveys indicate that up to one-third of cancer patients incur medical debt, of which 55% carry balances exceeding $10,000. In addition to debt and bankruptcy, credit scores are an important indicator of socioeconomic well-being following cancer diagnosis, because they affect housing stability, transportation access, and may even be predictive of health. Limited studies quantify incurred debt, bankruptcy rates, or credit scores following a cancer diagnosis compared with patients without a cancer diagnosis. Methods: Individuals with a cancer diagnosis in Massachusetts from 2010 to 2019 were identified through the Massachusetts Cancer Registry, and patient-level records on debt, bankruptcy, and other measures of financial well-being were linked using data from a major United States credit bureau. Changes in medical debt, credit score and bankruptcy filings were evaluated over time and compared with a random sampling of individuals residing in Massachusetts over the same time period that did not have a cancer diagnosis and were matched based on demographic factors. Results: 99,175 individuals with cancer and 188,875 individuals without cancer were identified, and average annual total debt balances were $758 and $669, respectively, throughout the study period. The highest total debt balances were observed among individuals with thyroid cancer ($913). Average annual medical collection balances were $45 for individuals without cancer and $52 among those with cancer with the highest balances among those with liver cancer ($66). Across the study period, the average annual bankruptcy incidence rate per 100 persons was 7.15 for those without cancer and 6.22 among those with cancer, with the highest incidence rates among those with thyroid cancer (7.34). Although there was a gradual increase in credit score in the control population, survivors of bladder, liver, ovarian, colorectal and lung cancers experienced a decline in credit scores. Conclusions: High rates of financial toxicity among individuals with cancer suggest that widespread healthcare and consumer finance reforms have not yet fully alleviated medical debt and bankruptcy in Massachusetts. Further research is needed to understand drivers of financial burden over time among those with cancer.
The toxicity swimmer plot: A novel approach for evaluating patient-level toxicity following immune checkpoint inhibitor (ICI) therapy on the Checkmate 214 trial.
Authors: Hollis Viray, Hui Huang, Charlene Mantia, Opeyemi Jegede, Michael B. Atkins, David F. McDermott, Meredith M. Regan
Journal: Journal of Clinical Oncology (2024)

11014 Background: Treatment with ICIs creates the possibility of prolonged disease control or remission but also creates the possibility of prolonged toxicity even after treatment is discontinued. Treatment-free survival (TFS) with and without toxicity has previously been described as an integral piece of a partitioned survival analysis in advanced renal cell carcinoma (aRCC). Prior analyses have reported further partition of TFS as mean duration of TFS with and without treatment-related adverse events (TRAEs), but this metric fails to provide more granular information regarding individual patients experiencing toxicity during TFS. We present a novel extended swimmer plot that characterizes patient-level toxicity data within TFS using the example of the Checkmate 214 trial to complement analyses of the population average experience. Methods: Data were analyzed from the Checkmate 214 trial which randomized 1096 patients with aRCC to receive either first-line (1L) nivolumab plus ipilimumab (n = 550) or sunitinib (n = 546). The minimum follow-up from protocol therapy initiation was 42 months. Patients’ overall survival was partitioned into 3 survival states: time on 1L protocol therapy, TFS, and survival after subsequent therapy initiation. With a re-defined time origin relative to cessation of 1L protocol therapy, we generated swimmer plots highlighting the TFS period and documenting each patient’s experience with and without grade 2+ and grade 3+ TRAEs during TFS. The swimmer plot was sorted by duration of TFS and duration of TFS with grade 2+ TRAEs in order to illustrate patterns of individuals’ experiences. Results: The 42-month mean TFS was 7.8 months (with grade 2+ TRAEs: 3.2 months) for patients treated with nivolumab plus ipilimumab and 3.3 months (1.6 months) for patients treated with sunitinib. In the respective treatment groups, TFS with grade 2+ TRAEs was experienced by 32% and 25% of patients and comprised of 13% and 9% of patients for whom it was the entire TFS period. These percentages were consistent regardless of TFS duration. TFS with grade 3+ TRAEs was experienced by 15% and 3% of patients, respectively. For most patients having TFS with TRAEs, the TRAEs persisted from the protocol therapy period, but 7% and 1% of patients in the respective treatment groups had new-onset grade 3+ TRAE during TFS. A swimmer plot will be presented as a visual presentation of this study’s results. Conclusions: We describe a novel extension of swimmer plots for presenting patient-level information and illustrating patterns in toxicity duration relative to TFS by incorporating individual toxicity data into a swimmer plot of partitioned survival. This approach allows for a more comprehensive understanding of toxicity trends and risk of prolonged toxicity after treatment is discontinued.
Effect of real-time data-driven physician engagement on appropriate precision oncology testing.
Authors: Ying Liu, Howard L. McLeod, Jeff Schreier, Nirmala Bhogal, Jordan Clark, Eve Thompson, Arun Rompicherla, Gemma Little, Joshua McKenna, Anjum Ismail, Sarah Varghese, Bethany Michelle Slifko
Journal: Journal of Clinical Oncology (2024)

11168 Background: Precision medicine is a paradigm shift in healthcare: 24% of all FDA approvals are precision medicines, with 67% of new approvals relying on companion or complementary testing or on diagnostics prior to clinical use. Yet a recent publication indicates that approximately 64% of potentially eligible patients could be lost due to various clinical practice gaps along patient journey (Sadik et al JCO 2022). Low prevalence biomarker testing is proven to be one of the critical determinants of missed therapy, potentially due to poor physician awareness. The increasingly advanced machine learning (ML) and natural language processing (NLP)-based ability to label, analyze, and segment data can be utilized to monitor and influence testing behavior in real-time. We hypothesize that a real-time data-driven physician-targeted digital engagement can increase biomarker testing rate and in turn enhance patient identification for precision therapies. Methods: Unstructured real-world, real-time biomarker testing reports were collected from 494 laboratories across the US. These testing reports were first curated, labeled and extracted via ML and NLP-based technologies to allow data analysis and reveal testing behavior. Suboptimal testing behavior was defined as no requisition of the selected novel biomarker as part of the diagnostic workups. Physicians who identified as having suboptimal testing behavior were selected as candidates to receive a personalized digital engagement over a 4-week period. The digital engagement's purpose was to raise clinical awareness towards the novel biomarker testing. The follow-up testing behavior was analyzed again over laboratory reports collected from 26-weeks’ time after the initial engagement. Results: 822 physicians were identified with suboptimal testing behavior and selected to receive 4 weeks' follow-up digital engagement. 271 out of 822 (33%) recipients were successfully engaged shown as open and read the digital communication. 42 (~15%) physicians reacted to the communications and ordered the new test at least once during this period. The initial 4 weeks' engagement was observed to be the most impactful, when 23 out of the 42 (~55%) physicians ordered the novel biomarker test for the first time.71 new therapy-eligible patients were identified via data-driven targeted physician digital engagement during the 26 weeks’ follow-up period. Conclusions: This study illustrates the value of data in influencing or reinforcing testing behaviors and emphasizes the value of data-driven physician-targeted digital engagement in addressing clinical practice gaps which in turn, drive patient identification to match potential eligible precision therapies.
Sensitivity and specificity of 61 commercial disease detection products: A systematic review and meta-analysis of 80 cohorts with approximately 445,000 enrolled samples.
Authors: Yujie Shi, Yingxiang Li, Shaochen Cheng, Tianliang Liu
Journal: Journal of Clinical Oncology (2024)

e22505 Background: In 2020, a total of 19.29 million newly diagnosed cancer cases and 9.96 million cancer-related deaths worldwide. Timely cancer detection through disease screening technologies is crucial to reduce the burden of cancer significantly. Methods: We compiled a list of products from industry reports on early screening products and retrieved published papers testing these products from relevant company websites. Results: A comprehensive list of 80 disease detection or early screening products currently available in the market. Out of these, 61 products had published research articles. The products comprised nine multi-cancer early detection (MCED) and 52 single cancer/disease early detection (SCED) products, encompassing 26 different cancer types. Blood was the most frequently used sample type. The sensitivity and specificity of the products ranged from 27.1% to 100% and 32.5% to 100%, respectively. Many products aimed to enhance predictive accuracy by integrating various types of information, resulting in a 9% increase in specificity compared to products using only single-type factor. The average sensitivity and specificity for MCED products were 69.2% and 96.6%, respectively, while for SCED, the values were 86.4% and 80.0%. A significant disparity was observed in the number of products for different cancers/diseases, each with unique sensitivity and specificity. Conclusions: An increasing number of cohort studies provide evidence that these products can serve as complementary tools for cancer/disease screening and diagnosis. In our opinion, an ideal product should strike a balance between safety, accuracy, convenience, and cost-effectiveness. [Table: see text]
Trichology to predict efficacy of scalp cooling: New pathologic insights besides encouraging clinical results.
Authors: Dorthe Schaffrin-Nabe, Anke Josten-Nabe, Andrea Tannapfel, Adrian Heinze, Merle Schaffrin, Rudolf Voigtmann
Journal: Journal of Clinical Oncology (2024)

12093 Background: Chemotherapy continues to be an essential element of tumour-specific systemic therapy. The associated hair loss impacts patients ‘quality of life in addition. Sensor-controlled scalp cooling has proven itself as a method of preventing alopecia. This study evaluates the grade of hair preservation as well as predictive factors, including (ultra)structural changes of the hair follicle during treatment, offering potential for enhanced therapeutic strategies. Methods: Scalp cooling, was evaluated in 81 patients (79 women, 2 men, median age 56 years) undergoing breast carcinoma treatment (4x EC 90/600 mg/m² BSA followed by 12x PAC w). Key outcomes included hair preservation (Hair Mass Index = HMI), avoidance of visible hair loss (HMI ≥ 50), and prevention of severe hair loss (all measured by Cross Section Trichometer). Parameters such as hair density (HMI), trichologic parameters like hair shaft and bulb diameter, anagen rate, shaft surface damage and melanosomes changes were measured through (ultrastructural) microscopy. Results: Over the half (53%) of patients avoided successfully noticeable hair loss (HMI post ≥ 50). Most important predictors of successful hair preservation in different analyses included lower post-therapeutic shaft surface damage (via scanning electron microscopy) (β = -.30, p = .034), larger pre-treatment shaft diameter (via light microscopy) (OR = 1.11, p = .011), and stable melanosome density (via transmission electron microscopy) (β = .35, p = .013). Higher anagen ratio (β = .30, p = 0.009) and larger hair shaft diameter (β = .29, p=0,023) plays a crucial role in hair prevention, considering only light-microspcopic parameters. Comorbidity (OR = 0.12, p = .024) and alopecia causing medication (e.g. antihypertensiva) (β = -.31, p = .017) led to increased hair loss. Patients with fewer hair loss over the course reported higher quality of life (r = .25, p = .042) and lower psychological burden (r = -.42, p &lt; .001). Data indicate that optimal pre-therapeutic hair density (HMI =/&gt; 69), coupled with the absence of comorbidities and alopecia-inducing medications, substantially enhances the efficacy of scalp cooling, elevating the probability of preventing severe hair loss (HMI ≥ 50) by nearly sevenfold (OR = 6.98, CI95% [1.01;48.33]. Conclusions: Scalp cooling proves effective in preventing visible hair loss in 53% of patients, with mini-organ (hair follicle) characteristics influencing outcomes. It does not only prevent hair loss but also enhances quality of life, underscoring the need for personalized approaches in managing chemotherapy-induced alopecia. The study confirms the method's safety and effectiveness without increasing scalp metastasis risk.