bluuebunny/crossref_metadata_2025 huggingface dataset:
Phase 3 RCT of dexamethasone versus placebo for chemotherapy induced fatigue in patients with advanced solid malignancies.
Authors: Radhakrishnan Venkatraman , Gopalakrishnan Vidhya , Vihari Vamsi , Dasapathi Venkata Siva Kiran Kumar , Rajaraman Swaminathan , Perumal Kalaiyarasi Jayachandran , Iyer Priya , Krishnamurthy Arvind , V Sridevi , Veeraiah Surendran
Published: June 2023

12112

Background: Short-term steroids (<2 weeks) have been used to alleviate fatigue in patients with advanced cancer. However, the efficacy and safety of long-term steroids (12 weeks) in patients with advanced cancer receiving palliative chemotherapy have not been studied. Methods: The study was an open-label, placebo-controlled, phase 3 RCT to evaluate the efficacy and safety of low dose dexamethasone (DEX) in reducing chemotherapy and cancer associated fatigue. Patients aged 18-60 years with performance status ≤2, undergoing palliative chemotherapy for advanced solid malignancies were randomized 1:1 to receive either DEX (4mg/day) or a placebo for 12 weeks. Fatigue was measured using the Symbolic Assessment of Fatigue Extent (SAFE) scale and EORTC FA12 scale, and quality of life (QOL) was assessed using the EORTC QLQ c30 at baseline, 6 weeks, and 12 weeks. The primary endpoint was to compare fatigue between the study arms at 6 weeks. Secondary endpoints were to compare fatigue at 12 weeks, QOL and toxicities. With a power of 80%, α of 5% (2-sided), 126 patients (including 25% drop-outs) were required to show the superiority of DEX in reducing SAFE fatigue extent score by 50% at 6 weeks. Results: A total of 126 patients were randomized (64 in the placebo arm and 62 in the DEX arm) between Oct 2018-Sep 2022. The median age was 46.5 years and 67% were females. Metastatic breast (28%) and lung (16%) cancer were the common diagnosis. Twelve and 23 patients in the placebo arm and 13 and 22 patients in the DEX arm did not undergo week 6 and 12 assessment respectively due to disease progression. The results showed no significant differences in mean SAFE scores, FA12 scores, or QOL between the study arms at 6 and 12 weeks, except for higher FA12 social sequelae in the DEX arm at 12 weeks (P=0.048) (Table). There were no significant differences in toxicities between the arms. Conclusions: The results of this study suggest that low-dose DEX is not effective in reducing chemotherapy associated fatigue or improving QOL in patients with advanced cancer. Clinical trial information: CTRI/2018/08/015222 . [Table: see text]
Unveiling inequities in palliative care and clinical trial participation among patients with metastatic breast cancer in the state of Florida.
Authors: Oladeru Oluwadamilola Temilade , Hong Young-Rock , Giap Fantine , Bradley Julie Ann
Published: June 2023

12120

Background: Persistent inequities in the care for patients with metastatic breast cancer (mBC) were recognized by ASCO and, in partnership with Pfizer, awarded our team a grant to understand and address them in people of color. Florida has a higher age-adjusted percentage of breast cancer in females and a higher mortality rate in those under the age of 65 compared to the United States. The racial disparity in mortality is further magnified among female patients with mBC. Therefore, we sought to characterize the prevalence and trends of palliative care utilization and clinical trial participation (CTP) among Floridians with mBC and quantify the associated factors. Methods: Using the OneFlorida+ Data Trust, a repository of patient-level electronic health records of ~17 million Floridians seen in public and private health care systems, including those enrolled in Medicaid, we obtained demographics of mBC patients, including sex, age, race, and ethnicity, insurance type, zip-code based socioeconomic status, Charlson comorbidity index (CCI) and rural/urban residence. CPT codes were obtained for palliative care services between the date of mBC diagnosis and death, including pain management, psychology, psychiatry, nutrition, and advanced care planning. Our analysis included the Cochran-Armitage trend test and bivariate analysis to correlate patient characteristics to palliative care receipt and CTP. Results: In Florida, 25,225 individuals (1.5% men and 98.5% women) were diagnosed with mBC between 2012 and 2021; 49.3% were under age 60. 19.5% of this cohort received palliative care at a median time of 10.1 months (IQR 2.1 – 27.1) from the initial diagnosis of mBC. The median survival was 13.6 months (IQR 3.4 – 31.6). On multivariable analysis, significant variables (p < 0.001) associated with increased palliative care utilization were Non-Hispanic Black, self-pay/uninsured and Medicaid insured, and a CCI of 5+. Only 3% of the study cohort had advanced care planning. There was a declining trend in CTP among patients with mBC, from 13.9% in 2012 to 7.9% in 2021. Among those participating in clinical trials, 80.2% did not receive palliative care. Variables associated with higher CTP (p < 0.001) were younger age (18-49), Asian and Hispanic race/ethnicity, the highest quartile of median household income and education level, private insurance, metropolitan residence, and CCI of 0. Further, there was a trend towards more prolonged survival among those enrolled in clinical trials. Conclusions: This robust statewide assessment highlights that less than 20% of patients with mBC receive palliative care, and its receipt is exclusive of CTP. We identified significant racial and socioeconomic disparities in CTP. Educational interventions with palliative care trained navigators, partnerships with providers on palliative care benefits, and state policy support are needed.
AI blood signature in common blood tests for detection of gastric cancer in a cohort of 190,000 individuals.
Authors: Wong Tsz Chun Bryan , Lam Serene JL , Cheung Ka Man , Sung Winnie , Woo Peter YM , Chow James CH , Yip Ada SM , Ng Stephen KK , Lee Martin SC , Kan Daisy MY , Kao SS , Yiu Harry HY , Lam David CC
Published: June 2023

1500

Background: Gastric cancer is the fourth leading cause of cancer death worldwide. Lack of symptoms in the early stage of disease leads to delayed presentation and low overall survival rate. Early detection is key, but there is not yet an established test for non-invasive gastric cancer screening. Routine blood test panels, including complete blood count, liver function, renal function and clotting profiles, could be potentially useful in reflecting bodily processes related to cancer. Current literature and territory-wide statistical data analyses from Hong Kong have shown these subtle changes and differences in measured levels of subcomponents between individuals with and without gastric cancer, that are not recognized clinically, form recognizable patterns distinct to gastric cancer. In this study, we hypothesized that gastric cancer signatures could be identified in routine blood data. Deep learning AI algorithms are used to identify the gastric cancer signature. Results from testing and validation of the identified routine blood signature using a Big Clinical Data cohort are reported. Methods: This is a territory-wide healthcare database study using data from Hong Kong Hospital Authority data collaboration laboratory. All patients prescribed with medications for dyspepsia and with all blood tests components (CBC, LFT, RFT, clotting function) available in the period between 2004-2015 inclusive were included. In the period, data from 2004 to 09 and 2011 to 14 were used as training cohort and the rest were used as testing cohort. A blood gastric cancer signature was generated using deep learning AI algorithms, and applied to predict gastric cancer in Big Data population. Results: 193,117 patients were included in the captioned period, in whom 4,790 patients were diagnosed to have gastric cancer. 151,449 (3,815 pts with gastric cancer and 147,634 pts disease free) patients were included In training cohort. In the testing cohort in 2010 and 2015 (975 pts with gastric cancer and 40,693 pts disease-free), the tumor signature yielded a sensitivity of 0.79, specificity of 0.99, positive predictive value of 0.95 and a negative predictive value of 0.99. Conclusions: The hypothesis of the presence of a distinctive gastric cancer signature from parameters in routine blood test data is tested and validated in a large population cohort with dyspepsia. The signature has high accuracy and high sensitivity with low false positive and false negative rates. Multicenter prospective testing is being conducted in cohort indicated for OGD in Hong Kong.[Table: see text]
Association of Medicaid expansion with treatment receipt, delays in treatment initiation, and survival among young adult women with breast cancer.
Authors: Han Xuesong , Shi Kewei Sylvia , Ruddy Kathryn Jean , Zhao Jingxuan , Mertens Ann C. , Yabroff Robin , Castellino Sharon M. , Ji Xu
Published: June 2023

1509

Background: Medicaid expansion under the Affordable Care Act has been shown to increase insurance coverage and early-stage cancer diagnoses for young adults (YAs), the age group with the highest uninsured rate. We examined whether Medicaid expansion was associated with increased receipt of timely, guideline-concordant treatment and survival among YA women newly diagnosed with breast cancer, the most common YA cancer diagnosis. Methods: Using the National Cancer Database, we identified 51,675 women aged 18-39 years who were diagnosed with breast cancer in 2011-2018. We applied the difference-in-differences (DD) method to estimate outcome changes pre vs. post Medicaid expansion, in expansion- vs. non-expansion states. Linear probability models estimated associations of Medicaid expansion with receipt of guideline-concordant treatment – including any endocrine therapy among women with ER-positive or PR-positive breast cancer, and any chemotherapy or targeted therapy among women with ER-negative and PR-negative breast cancer – and initiation of guideline-concordant treatment (surgery, chemotherapy, or targeted therapy for stage I-III diagnoses, and systemic therapy for stage IV diagnoses) <60 days after diagnosis. Flexible parametric survival models were used to estimate 2-year overall survival. DD models also adjusted for age, race/ethnicity, rurality, zip code-level income, comorbidity, and diagnosis year, with standard errors clustered at the state level. Analyses were stratified by stage at diagnosis (stage I-III vs. IV). Results: Of the subset of women with stage I-III ER-positive or PR-positive breast cancer, the percentage receiving endocrine therapy increased in expansion states (85.20% pre-expansion to 86.46% post-expansion), but decreased in non-expansion states (84.32% to 82.79%), resulting in a net increase of 2.42 percentage points (ppt; 95% CI = 0.56 to 4.28) associated with Medicaid expansion in the adjusted DD model. Among all women with stage I-III breast cancer, the percentage with treatment initiation <60 days after diagnosis decreased less in expansion states (84.10% pre-expansion to 82.36% post-expansion) than in non-expansion states (86.95% to 83.98%), resulting in a net reduction of 1.61 ppt (95% CI = 0.05 to 3.18) in treatment delays associated with Medicaid expansion. Notably, the 2-year overall survival increased in expansion states (96.84% pre-expansion to 96.99% post-expansion), but decreased in non-expansion states (97.24% to 96.30%), resulting in a net survival increase of 1.00 ppt (95% CI = 0.21 to 1.79) associated with Medicaid expansion. Conclusions: Among YA women with stage I-III breast cancer, Medicaid expansion was associated with increased receipt of guideline-concordant treatment, reduced delays in treatment initiation, and improved 2-year survival.
Dose rounding bevacizumab and its biosimilars to reduce drug waste in the oncology care model in a community oncology network.
Authors: Indurlal Puneeth , Alam Naiyar , Garey Jody S. , Wilfong Lalan S.
Published: June 2023

1529

Background: The Oncology Care Model (OCM) was a 6-year long Medicare value-based care (VBC) program that rewarded practices for decreasing TCOC compared to a benchmark price, while maintaining high-quality cancer care. Drug waste from partially used single dose vials (SDV) of expensive anti-neoplastic agents is a leading contributor to avoidable Total Cost of Care (TCOC) expenditures for payers. Dose rounding (DR) of biological anti-neoplastic agents, using recommendations (https://www.nccn.org/docs/default-source/clinical/order-templates/hopa.pdf?sfvrsn=3af91118_6) from the Hematology Oncology Pharmacists Association (HOPA) and endorsed by the National Comprehensive Cancer Network (NCCN), is a standard approach to mitigate the impact of drug waste. Many of the practices in The US Oncology Network (The Network) adopted a DR program for biologic agents in 2018 as a strategy to reduce drug waste and TCOC. We studied the impact of a DR initiative targeting bevacizumab and its biosimilars (B+B) on TCOC and drug waste expenditures for The Network practices participating in the OCM. Methods: Claims data for 14 practices in The Network participating in the OCM were assessed. Drug administration data for B+B was used to evaluate drug waste, total dose, TCOC, DR and the financial impact of drug waste reduction on TCOC from 2017 to 2021. Results: In 2017, prior to implementing DR, an average of 5.3% (range 4.6% to 5.5%) of the total dose of B+B was wasted, with ~25% of B+B administrations having waste in excess of 10% of the total dose. Implementation of the initiative led to a reduction of waste on 30% of the total administrations of B+B across 14 OCM participant practices in The Network. As a result of DR, B+B drug waste decreased by 55% to an average of 2.5% (range - 2.3% to 2.7%) of the total dose in 2021. Decreasing drug waste resulted in TCOC reduction of approximately $100 per member episode per month (0.97% of TCOC) for episodes with B+B administrations in the OCM. The highest waste reduction was seen with B+B administered for treatment of gastrointestinal cancers (colon, rectal, anal, gastroesophageal, or pancreatic cancers) compared to other cancer types (lung, brain, ovarian, etc.), and for B+B administrations where drug waste was greater than 10% of the total dose (~50% reduction). Conclusions: Drug waste contributes avoidable expenditures to the TCOC. Implementing strategies such as DR can offset the impact of drug waste and offer meaningful TCOC savings for VBC programs such as the OCM. A similar DR approach may be adopted for other high-cost biologic agents where drug waste results from partial use of SDVs.
Implementation of a streamlined prior authorization process to improve cancer care delivery.
Authors: Bhardwaj Aarti Sonia , Liu Mark , Pintova Sofya , Williams Chanda , Liggins Jennifer , Soto Haydee , Favre Daniel , Noble-Kirk Alana , Smith Cardinale B.
Published: June 2023

1531

Background: Prior authorizations (PAs) for systemic cancer treatments are increasingly becoming a barrier to timely quality cancer care delivery. There is an extraordinary administrative burden placed on clinicians to complete peer to peers (P2P) and appeals when authorization specialists are unable to identify appropriate clinical data in the EHRs. This leads to delays in care, staff burnout and loss of revenue. At our tertiary academic cancer center, in partnership with our cancer registry and Epic teams, we propose shifting the clerical work required for intravenous chemotherapy PAs from clinicians to certified tumor registrars (CTRs) to improve documentation needed for authorization specialists and decrease PA associated clinician burnout. Methods: Clinicians first place the treatment plan order which goes to the CTR work queue. We leveraged the Epic staging smart form to consolidate and auto-populate a list of common data elements needed for PA (performance status, cancer biomarkers, stage, line of treatment, and goals of treatment). The CTRs then complete and validate all elements necessary for authorization specialists to obtain the PA. Our primary outcomes include: average monthly number of intravenous chemotherapy authorizations pending review (including P2P, appeals and authorizations requiring other clinical interventions from the primary team) during a pre (9/1/2021-9/30/22) and post-implementation (11/14/22-1/30/23) period. Analyses were conducted using descriptive statistics. Results: The average monthly number of authorizations pending review was 332 pre-implementation and 227 post-implementation, which is a 32% reduction. To account for temporal changes, when comparing December 2021 to January 2022 vs December 2022 and January 2023, the average number of referrals pending review was 276 vs 227 which is an 18% reduction. First line treatment regimens accounted for most regimens requiring review; 28% and 27% pre-implementation and post-implementation, respectively. Non-chemotherapeutics like lanreotide and feraheme had the highest pending review status pre-and post-implementation respectively. Among chemo/immunotherapeutics, Nivolumab and Trastuzumab deruxtecan had the highest pending review status pre and post implementation, respectively. GI regimens had the highest number of regimens requiring review accounting for 17% vs 22% of all referrals pre and post implementation, respectively. Conclusions: By leveraging technology and increasing efficiencies of existing non-clinical staff workflows, we significantly decreased the number of ambulatory chemotherapy PAs that required further clinical review including P2P and appeals thereby improving efficient care delivery. Next steps include evaluation of sustained improvement, time to final authorization, revenue analysis and the impact on the well-being of clinicians.
Outcomes on the hematology malignancy hospitalist service: A model for inpatient care.
Authors: Kessler Alaina J. , Bhardwaj Aarti Sonia , Kisswany Carol , Sheng Tianxiang , Scott Lauren , Prystupa Olga , Reyna Maria , Kremyanskaya Marina , Smith Cardinale B.
Published: June 2023

1536

Background: The use of oncology hospitalists has been shown to improve quality outcomes among hospitalized patients, though there is limited data on the use of hospitalists to care for patients with hematologic malignancies. The Hematology Malignancy Hospitalist Service (HMHS) was created in efforts to decrease patient volume on the primary hematology malignancy services at an academic hospital. Patients with active oncologic issues requiring specialty oncology management were cared for by oncologists on the primary leukemia, lymphoma, and myeloma services while patients with acute medicine-related issues were cared for by medicine hospitalists on HMHS. Methods: Criteria were established based on level of acuity and reason for admission to HMHS, which was comprised of a hospitalist attending and nurse practitioner. New admissions to HMHS were evaluated by the primary hematology malignancy service team as consultants and remained involved in patient care as deemed appropriate. Oncology attendings continued to care for patients on the primary leukemia, lymphoma, and myeloma services. We conducted a retrospective analysis from 6/28/21 through 6/30/22 excluding 1/2/22 to 2/6/22 when HMHS was paused due to the COVID Omicron surge. We compared length of stay (LOS), discharge before noon (DBN), and 30-day readmission rates of patients admitted to the HMHS service and those admitted to the primary services to assess for differences in outcomes. Results: There were a total of 95 (12%) admissions to HMHS and 669 (88%) to the primary services; 35.6% patients were white, 21.7% Black, and 10.3% Asian and 26.3% patients identified as Hispanic. The average age was 61.6 years. The average LOS in days was 9±9.09, 16.03±14.96, 11.41±14.88, and 12.68±11.40 (p = 0.005) for patients admitted to HMHS, leukemia, lymphoma and myeloma services, respectively. DBN on HMHS (6%) was similar to the leukemia service (6%) and improved compared to the lymphoma service (11%) and myeloma service (7%); p = 0.66. The 30-day readmission rate was also improved on HMHS (12%) compared to leukemia (21%), lymphoma (21%), and myeloma (18%); p=0.25. Conclusions: The development and implementation of a medicine hospitalist-driven hematology malignancy service significantly improved LOS without a negative impact on 30-day readmission rates when compared to a primary hematology malignancy service model. The addition of medicine hospitalists to the inpatient care of patients with hematologic malignancies demonstrates improvement in healthcare utilization. This is an important area for future evaluation to determine the most appropriate patients to admit to these services and assess other important outcomes.
National lung cancer screening rates among women veterans within the Veterans’ Health Administration.
Authors: Bail Jennifer , Kommalapati Ajitha , Dell'Italia John , Das Devika Govind
Published: June 2023

1543

Background: Lung cancer is the number one cause of cancer related death among women in the United States. United States Preventive Services Task Force (USPTF) lung cancer screening (LCS) guidelines recommend annual low dose computed tomography (LDCT) among high-risk populations. The data specifically on women veterans is sparse so we retrospectively examined LCS rates among women veterans within the VHA. Methods: Women veterans ages 50-80, current or former (quit within 15 years) smokers from 2013- 2021 were identified through the VA corporate data warehouse (CDW). Captured characteristics included: demographics, smoking history, and cancer screening history (lung, breast, cervical). Data was analyzed using R Studio software. Results: Women veterans with a history of smoking (n=40,299) tended to be aged ≥60, white (66%), single (69%), unemployed (64%), urban dwelling (67%), and residing in Southeast U.S. (31%). Overall, cancer screening rates among women veterans was low (9% lung; 27% breast; 21% cervical). Of the women not screened for lung cancer (91%; n=36,837), 11% (n=4, 016) had a personal history of cancer. While pack-year history was not documented for the vast majority (92%), 7% (n= 2, 729) reported a >30 pack-year smoking history (guideline at the time). Of these >30 pack-year smokers, 88% (n=2,418) were not screened for lung cancer. Other significant demographic predictors of increased LCS rates included Southeast Veterans Integrated Service Network (VISN region) and comorbidities such as bipolar disorder and diabetes likely due to increased exposure to healthcare. Conclusions: LCS rates, as well as breast and cervical, among women veterans within the VHA is low. The lack of documented pack-year history among women veterans with a history of smoking is concerning. Increased documentation of pack-year history may aid in identifying women for LCS. Efforts are ongoing nationally to implement an equitable centralized LCS program for all veterans and as part of that effort the Birmingham VA Health Care System has utilized their Lung precision Oncology program (LPOP) funding to pilot a structured lung cancer screening program within our Women’s Health Clinic in 2022.
Effect of an oncology care management program on unplanned hospital admissions in a commercially insured population.
Authors: French Wendy L. , Beagley Callie B , Stevens Erica , Parker Elizabeth R , Norrell Angelica I , Doelger Lisa A , Flood William A. , Latts Lisa M
Published: June 2023

1547

Background: Despite advances in cancer outcomes, costs of cancer care continue to rise. Acute care utilization contributes significantly to these costs. The Cancer Support Program’s (CSP) care management services focus on providing education on symptom management, palliative care and advance care planning, addressing psychosocial needs and closing gaps in care in members with cancer who are at high risk for unplanned hospital admissions (UHA). Methods: Beginning 1/1/22, commercially insured members with an active cancer diagnosis were clinically stratified as high or low risk for UHA. All high-risk members were invited to participate in the CSP program. Individuals who agreed to participate received individualized telephonic care management support. Medical claims from 1/1/22 through 9/30/22 were evaluated, and rates of UHA were compared between participants and non-participants within the identified high-risk population for an average period of 4 months after identification (the period equivalent to the average enrollment period of participants). Results: The study population included 3,113 members who stratified as high risk. Of those, 36% were enrolled in the program. Reasons for non-enrollment include inability to reach (72%), member refused (27%) and bad contact information (1%). There were no statistically significant differences between the two groups’ demographic composition except for age (the enrolled group had slightly more in the 51-64 age group [63% vs. 59%; p < 0.001] and slightly fewer in the > 65 age group (9% vs. 15%; p < 0.001]). There were 358 UHA in the participating group and 737 UHA in the non-participating group. When normalized, there were 1,179 UHA per thousand members per year (PTMPY), 99% CI [1,171 UHA, 1,184 UHA] (bootstrap) in the participating group and 1,526 UHA PTMPY, 99% CI [1,523 UHA, 1,535 UHA] (bootstrap) in the non-participating group. Conclusions: Early results show lower UHA rates for members who participated in the care management program, suggesting the program is effective in reducing acute care utilization within the high-risk population. Limitations of this study include potential enrollment bias, changes in risk status from clinical or social factors, and the potential for human error or inconsistency in the risk stratification process. Further study is underway to validate these results.
Lost in translation? Information exchange during breast cancer care and implications for technology design.
Authors: Salwei Megan , Reale Carrie
Published: June 2023

1558

Background: Almost 4 million women in the US have had breast cancer, with 300,000 women diagnosed each year. Treatment decision-making following breast cancer diagnosis can be challenging as there are often several clinically appropriate treatment options, each with differing impacts on patient short- and long-term quality of life. Further, patients must manage this information during a time of high emotional burden, which can hinder decision-making. Not surprisingly, studies have found that less than 50% of patients believe their treatment plan aligns with their preferences. Numerous decision aids have been developed to support patient decision-making. However, sustained use of decision aids is limited due to poor integration in clinical workflow. We need to better understand the complex workflows and needs of decision aid users - patients and breast cancer clinicians. In this study, we investigate the information exchange between patients and clinicians when making breast cancer treatment decisions and identify design requirements for patient-centered decision support tools. Methods: This study is part of a larger research project to design a COMputerized PAtient-centered Collaborative Technology (COMPACT) to support personalized breast cancer decision-making. We observed clinicians at one academic medical center’s breast center from February-August 2022. Participating clinicians were followed throughout their clinical shift. Using a tablet computer and smart pencil, we recorded all aspects of clinician workflow. Written notes were transcribed and uploaded into Dedoose. Two human factors researchers inductively coded each observation in a consensus-based process. Results: We observed 79 hours of clinical care and 119 patient encounters across 20 observations of various clinical roles. Overall, we found that patients with breast cancer must manage an enormous amount of highly complex information that includes technical medical terms, mathematical concepts (e.g., risk), and uncertainty. We identified over 20 distinct decisions that patients face during their cancer journey, which were interdependent and evolved over time. We identified numerous patient-specific factors that influenced treatment decision-making, such as the patient’s work and family circumstances. For instance, one patient was organizing a conference and needed to plan her surgery around this event. Patients were frequently asked to remember and relay information across members of the care team, indicating inadequate system support of information transfer within the large cancer team. Based on these findings, we identified design requirements for interventions to support care coordination and patient-centered decision-making. Conclusions: These findings can inform the design of interventions to support breast cancer decision-making and improve patient-centered cancer care.
Accuracy of a clinical decision support system in identifying patients at risk of cancer in primary care.
Authors: Bakshi Bea , Payling Miles
Published: June 2023

1562

Background: 85% of patients diagnosed with cancer are symptomatic at presentation. Yet a delay in diagnosis (e.g. missing a presentation) can result in late stage detection and poorer outcomes. Clinical decision support systems (CDSS) have been used in other fields to calculate risk and support standardization of care. However, little has been reported about successful implementation of CDSS with determining cancer risk. C the Signs is a CDSS which uses artificial intelligence, mapped with the latest evidence and guidance, to assist healthcare professionals in identifying patients at risk of cancer and determining the most appropriate pathway for diagnosis. The aim of this study is to assess the accuracy of C the Signs in a real-world setting. Methods: A retrospective observational study was conducted in the National Health Service in England utilizing all patients risk assessed for cancer through the Electronic Healthcare Record (EHR) integrated C the Signs platform between 1st January 2021 and 31st August 2022. A total of 118,677 patients were risk assessed. All patients were followed up for 6 months post risk assessment to determine outcome. A sub-analysis was performed on the patients who were flagged at risk of cancer through C the Signs and subsequently diagnosed with cancer to establish the CDSS’s cancer origin accuracy (the ability for the system to accurately predict which cancer the patient is at risk of). Results: 7,295 patients were diagnosed with cancer within 6 months of a C the Signs risk assessment. 7,056 patients were successfully identified at risk of cancer by the CDSS with a sensitivity of 96.7%. There were 103,168 false positives with a specificity of 7.37%. Of the 8,453 patients who were identified as not at risk of cancer using the CDSS, 239 had a confirmed cancer diagnosis within 6 months of risk assessment (with a negative predictive value 97.2%). The cancer origin accuracy of C the Signs was 85.6% across all cancers. Conclusions: A cancer CDSS like C the Signs can be used to accurately identify patients at risk of cancer. More research is needed to understand the specificity and false positive rate, and the impact of identifying these patients with non-cancer disease.
Deep learning to estimate RECIST in patients with cancer treated in real-world settings.
Authors: Riaz Irbaz Bin , Ashraf Noman , Harris Gordon J , Choueiri Toni K. , Kehl Kenneth L.
Published: June 2023

1564

Background: Creating large oncology clinical-genomic datasets is laborious and time-consuming. Deep learning approaches that extract RECIST outcomes at scale from observational electronic health records (EHR) data could tremendously facilitate precision oncology research. Methods: This retrospective study included patients with solid tumors treated on therapeutic clinical trials from 2004-2022 at Dana-Farber Cancer Institute with radiology reports in EHR and RECIST labels available from the tumor imaging metrics core. Each RECIST label was generated using corresponding radiology reports at a given time point. Patients were sampled into training, validation, and held-out test sets. A deep learning model (RECIST model) was trained to predict two outcomes: overall response and progressive disease at each time point, using reports from that time point and prior time points for each patient. This trained RECIST deep learning model was deployed on real-world radiology reports, and results were compared with true labels abstracted by trained human curators using the PRISSMM framework. Results: This study included 5153 patients with a total of 99,318 radiological reports who had RECIST annotations (median age at protocol enrollment [IQR] 60 years [52-57]; females 61% [3133]; and white 90% [4653]). The most common cancer types included breast (n=1006; 20%) lung (n=573; 11%), and ovarian cancer (n=539; 10%). The training subset included 4121 (79.9%) patients, the validation subset 518 (10.1%), and the held-out test set 514 (9.9%) patients. In the test set, the results showed an AUC of 0.86, and 0.87 with the best F1 scores of 0.72 and 0.63 for predicting overall response, and progressive disease, respectively. The real-world data set included 4482 patients. RECIST model evaluation on real-world radiology reports showed good performance for ascertaining PRISSMM annotations of progression from those reports (AUC 0.83, best F1 0.68), but poor performance for ascertaining PRISSMM annotations of response (AUC 0.63, best F1 0.28). Evaluation metrics are outlined in the Table. Conclusions: This study demonstrated the feasibility of using deep learning approaches to predict RECIST outcomes from radiology reports for patients with solid cancer tumors. The results show that the deep learning model accurately predicted RECIST labels on a held-out test set and real-world radiology reports for the outcome of progressive disease. These findings could accelerate precision oncology research providing a scalable way of ascertaining cancer outcomes from observational EHR data.[Table: see text]
Trends in U.S and global patient enrollment from 2014 to 2022 in lung cancer clinical trials supporting marketing applications: An FDA analysis.
Authors: Akinboro Oladimeji , Kumar Vaibhav , Drezner Nicole Lauren , Larkins Erin A. , Pazdur Richard , Kluetz Paul , Singh Harpreet
Published: June 2023

1576

Background: Oncology drug development is an increasingly global endeavor, however it is unclear how enrollment in registrational clinical trials for lung cancer have been impacted. Clinical trial data must be reflective of the intended population in order to be considered applicable to U.S patients and medical practice, and for FDA review. Methods: Registrational clinical trials supporting lung cancer indications submitted to FDA from 2014 to 2022 were included. Patient enrollment per country was extracted for each trial, and countries were grouped into 9 global regions. The proportion of patients enrolled in the U.S and global regions were calculated for each trial. For the purpose of this analysis, MRCTs were defined as trials that enrolled at least 5% of patients from each of ≥ 3 global regions with no region accounting for ≥ 70% of patient enrollment. Trial-level patient enrollment was aggregated into 3 triennia: 2014-2016, 2017-2019, and 2020-2022. Results: A total of 66 pivotal trials supporting 59 applications submitted to FDA were evaluated during the study period. Of these, 91% ( n=60) were for non-small cell lung cancer while 9% ( n=6) were for small cell lung cancer; 59% ( n=39) were randomized controlled trials (RCTs) while 41% ( n=27) were single-arm trials; 53% ( n=35) were for biologics while 47% ( n=31) were for non-biologics; and 86% ( n=30) of the biologics-based regimens were anti-programmed death (ligand)-1 antibody-containing regimens. The proportion of trials with no U.S patient enrollment increased from 4.8% in 2014-2016 to 19.0% in 2020-2022 while those with ≥ 10% U.S patient enrollment declined from 71.4% in 2014-2016 to 52.3% in 2020-2022. There was a decline in the proportion of trials conducted as MRCTs since 2014 from 85.7% in 2014-2016 to 66.7% in 2020-2022. Conclusions: This exploratory analysis suggests that there may be declining U.S patient enrollment in lung cancer pivotal trials, and the proportion of these trials conducted as MRCTs may also be declining. These patterns of decline appear to be driven by the countries selected for patient enrollment in RCTs rather than in single-arm trials. Pivotal trials that do not enroll U.S patients and are not conducted as true MRCTs may have limited applicability to U.S patients.[Table: see text]
Completion rates and trends of the patient-reported outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) across 14 oncology clinical trials.
Authors: Emerson Jessica A , Hughes Lindsay , Dumais Kelly
Published: June 2023

1579

Background: With growing emphasis on patient-centered regulatory decision making, there is a greater need to incorporate the patient’s voice in oncology clinical trials. Regulatory guidelines outline core patient-reported outcomes (PROs) to include which can inform risk/benefit evaluation. Self-reported symptomatic adverse events (AE) form part of these core PROs, with the new 2023 draft FDA guidance acknowledging the benefits of including them to enhance the assessment of tolerability in early phase dose optimization trials. Given the clinical symptoms and disease burden in oncology, patient burden needs to be thoughtfully considered when incorporating PROs into trials. We assessed trends and feasibility of electronic data collection for symptomatic AEs by analyzing completion compliance and time to complete the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) across 14 oncology trials. Methods: All PRO-CTCAE were collected electronically on Clario Tablets. Operational data for completion status (completed or missed) and duration of time to complete the PRO-CTCAE in seconds was extracted. Completion rates over time were examined overall and for every 3-month interval (quarters Q1 to Q9+). The median was selected for analyses of time to complete to account for skewness. Results: The sample included 14 studies across Phase I-III trials across a range of cancers including multiple myeloma, mesothelioma and cancers of the lung, prostate, head/neck, gastric, breast, and ovary. Study durations were 24 weeks and up. The PRO-CTCAE form was completed 13,122 times and missed in 1,182 instances, giving an overall completion rate of 91.7%. On average, 25 questions (range 5-47) covered an average of 13 symptoms (range: 4-25). Completion rate was not associated with the number of questions asked or time since enrollment. The overall median time to complete the PRO-CTCAE was 82s (study-specific median range: 24s to 276s). Examining time to completion as a function of the number of questions revealed a significant positive association, such that each additional question added 5.2 seconds to the time it took to complete the assessment. Conclusions: Completion compliance was high for PRO-CTCAE and remained high regardless of study length and the number of questions included in the PRO-CTCAE form. This suggests that electronic PRO-CTCAE is a feasible solution for collecting self-reported symptomatic AEs. Although time to complete the form increased with the number of questions, results suggest that including a higher number of PRO-CTCAE questions does not negatively impact compliance rate. Our data showing high completion rates may also reflect the benefits of electronic PROs in reducing patient burden and enhancing data quality, as acknowledged by regulatory agencies.
Patient-reported usefulness of an intervention to promote job retention among women undergoing (neo)adjuvant breast cancer chemotherapy.
Authors: Blinder Victoria Susana , Finik Jackie , Patil Sujata , Narang Bharat , Claros Maria , Suarez Jennifer , Martinez Samantha , Muppidi Monica , Makower Della F. , Gillis Theresa , Kuo Ting-Ting , Gany Francesca
Published: June 2023

1586

Background: Women who undergo (neo)adjuvant breast cancer chemotx are at risk of job loss, especially if they lack work accommodations. We developed TEAMWork (Talking to Employers And Medical staff about Work), an English/Spanish mobile application (app) to help women identify work accommodations relevant to their needs, negotiate with their employers to receive these accommodations, and communicate with the clinic team to manage symptoms. TEAMWork will be compared to a booklet as a job-retention tool in an ongoing randomized clinical trial (RCT). Here we present acceptability data based on RCT participants’ perceptions of the app’s usefulness. Methods: Eligible participants were women aged 18-64, who spoke English/Spanish, were able to use and had access to a smartphone/tablet, were undergoing or planned to undergo (neo)adjuvant chemotx for stage I-III breast cancer, and were working full or part time for pay. Women who had stopped working due to the diagnosis were eligible. Those who had stopped working for reasons unrelated to breast cancer (e.g., prior illness disability) were ineligible. Online surveys were self-administered or administered interview-style (per participant preference) at baseline and midway through the planned chemotx. In the second survey, participants were asked if they had used TEAMWork at all since enrollment; those who said they had used it were asked about the app’s usefulness. Results: 58 participants received the app; 56 received the booklet. 64% were white, 18% were Black, and 12% were Asian; 7% were Hispanic. 4% were Spanish-speaking. 79% had at least a college education. When surveyed half-way through their chemotx regimen, 62% of those randomized to the app said they had used the app; only 25% of those randomized to the booklet said they had used the booklet (p<0.0001). Among those who reported having used the app (n=36), 86% said they were very (44%) or somewhat (42%) satisfied with TEAMWork, and 94% said they thought TEAMWork would be very (61%) or somewhat (33%) helpful to other patients. Additional details about the perceived usefulness of the app are shown. Conclusions: Compared to participants randomized to the booklet, more than twice as many who received the app reported that they had used their assigned intervention. Among those who used it, the app was well-received and was deemed especially helpful for communicating with medical providers. Recruitment to the RCT is ongoing, and job retention results will be presented when data are mature. Efforts are under way to increase the diversity of the study sample based on ethnicity, language, and education. Clinical trial information: NCT03572374 .[Table: see text]
Association of accelerated approval (AA) status with National Comprehensive Cancer Network (NCCN) guideline recommendation for cancer drug indications: A cross-sectional study.
Authors: Cliff Edward Robert Scheffer , Rome Rachel S , Kesselheim Aaron S , Rome Benjamin N
Published: June 2023

1599

Background: Many oncology drugs are approved via FDA’s accelerated approval pathway based on trials showing changes to surrogate measures only ‘reasonably likely’ to predict clinical benefit. Despite this preliminary evidence, accelerated approval drugs are incorporated into clinical practice and included in guidelines. We assessed NCCN evidence and preference ratings for drugs with accelerated vs traditional approval. Methods: Accelerated approval oncology drugs were identified using an FDA list as of June 30 2022. Drug labelling revealed other oncology indications of these drugs. Accelerated approvals were stratified if they had been converted to traditional approval after confirmatory studies or withdrawn. Indications with no NCCN guidelines or tumor-agnostic approvals were excluded. Relevant NCCN guidelines were reviewed as of Oct 19 2022. Each indication was assessed for ratings of level of evidence and treatment preference. Levels of evidence included category 1 (consensus, high-level evidence), 2A (consensus, lower-level evidence), 2B (lower-level evidence without consensus), or 3 (major disagreement). Treatment preference rankings included preferred, alternative preferred, other recommended, or useful in certain circumstances. Results: Among 315 indications for 100 drugs, 156 (50%) had traditional approval and 159 (50%) had current or previous accelerated approval. Among accelerated approval indications, 78 (49%) had been converted to traditional approval and 21 (13%) withdrawn. Among all indications, 105 (33%) were rated as category 1 evidence, 185 (59%) as 2A, 6 (2%) as 2B, and 2 (0.6%) as 3. The treatment preference for 153 (49%) was preferred, for 55 (17%) was recommended, for 5 (2%) was alternative preferred, and for 38 (12%) was useful in certain circumstances. Compared to traditional approval, accelerated approval indications less often had category 1 evidence (3% v 47%), and were less often listed as preferred (40% v 58%). Converted accelerated approval indications had mid-range ratings for evidence (38% category 1) and treatment preference (47% preferred). 11 withdrawn accelerated approval indications remained in NCCN guidelines. Conclusions: In most cases, NCCN guidelines identified accelerated approval indications as having lower evidence than traditionally approved cancer drugs. Many traditional approvals and conversions from accelerated approvals had only category 2A evidence, suggesting better evidence is needed for traditional approval of oncology drugs. But in about half of accelerated approval indications withdrawn by the drug’s manufacturer, NCCN continued recommending the drug. Professional organizations like NCCN should ensure their guidelines reflect that accelerated approval drugs are being marketed based on preliminary evidence.