bluuebunny/crossref_metadata_2025 huggingface dataset:
Sequential use of PI3K/AKT/mTOR pathway inhibitors alpelisib and everolimus in patients with hormone receptor-positive (HR+) metastatic breast cancer.
Authors: Shen Sherry , Safonov Anton , Bromberg Maria , Chen Yuan , Ahmed Mehnaj , Razavi Pedram , Jhaveri Komal L.
Published: June 2024

1057

Background: Alpelisib (A), a PI3K inhibitor, is FDA-approved with fulvestrant for patients with PIK3CA-mutated HR+/HER2- MBC. Everolimus (E), an mTOR inhibitor, is FDA-approved with endocrine therapy (ET) regardless of PI3K/AKT/mTOR pathway mutation status. The efficacy and safety of sequential treatment with these pathway inhibitors is not well described. Methods: This single-center retrospective cohort study identified patients with HR+/HER2- MBC treated with both A and E sequentially, each in combination with ET, in either order from 2012-2023. We collected information on patient demographics, clinical and pathologic characteristics, treatment history, treatment adverse effects, and dates of disease progression (defined as radiographic or clinical progression leading to treatment change) from medical records. Patients treated first with E then A were categorized as Group 1 and those first with A then E as Group 2. Rates of prior CDK4/6i use were compared between groups with the chi-square test; differences in prior lines of therapy were assessed with the Wilcoxon rank sum test. Median PFS1 (PFS on 1st pathway inhibitor) and PFS2 (PFS on 2nd pathway inhibitor) were computed using the Kaplan-Meier method and the impact of prior treatment on PFS2 between groups was compared using Cox proportional hazards analysis. Results: 115 patients with HR+/HER2- MBC were included in this study. There were 62 (54%) patients in Group 1 and 53 (46%) patients in Group 2. Median prior lines of therapy in the metastatic setting for Group 1 was 4 (range 1-13) and for Group 2 was 3 (range 1-8; p=0.08). Median number of intervening therapies between E and A in Group 1 was 2 (range 0-8) and between A and E in Group 2 was 0 (range 0-4; p<0.001). 34/62 (55%) patients in Group 1 and 45/53 (85%) in Group 2 received prior CDK4/6i ( p<0.001). In Group 1, 49/62 (79%) of patients discontinued E for progression and 13 (21%) discontinued for toxicity. Median PFS1 was 9.2 months (95%CI 5.5-13.0) and PFS2 was 5.0 months (95%CI 4.6-7.9). In Group 2, 34/53 (64%) of patients discontinued A for progression and 19 (36%) discontinued for toxicity. Median PFS1 was 9.3 months (95%CI 7.0-14.0) and PFS2 was 3.5 months (95%CI 3.0-4.1). After adjusting for prior CDK4/6i use and prior lines of therapy (total and intervening), PFS2 was not significantly different between the groups. Genomic information will be included at the time of presentation. Conclusions: This is the largest retrospective study to-date of patients treated sequentially with PI3K/AKT/mTOR pathway inhibitors. PFS was longer with the 1st pathway inhibitor than with the 2nd regardless of sequence. This has implications for optimal integration of capivasertib, an AKT inhibitor, into HR+ MBC treatment. Prospective studies testing optimal sequencing are needed.
Efficacy of subsequent treatments after disease progression on CDK4/6 inhibitors therapy in patients with hormone receptor-positive metastatic breast cancer: A Kaplan-Meier derived individual-patient data meta-analysis.
Authors: Ravani Lis Victoria , Calomeni Pedro , Vilbert Maysa , Madeira Thiago , Wang Ming , Deng Daxuan , Testa Laura , Clifton Katherine , Wander Seth Andrew , Lustberg Maryam B.
Published: June 2024

1065

Background: Cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) combined with endocrine therapy (ET) are standard-of-care for patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/ HER2-) metastatic breast cancer (mBC). Yet, disease progression is common in these patients. In the absence of established guidelines for optimal sequencing post-progression, we conducted a pooled analysis of patient data to assess the efficacy of subsequent treatment options following disease progression on CDK4/6i therapy. Methods: We conducted a systematic review and meta-analysis, searching PubMed, Embase, Cochrane, and conference proceedings for randomized controlled trials (RCTs) and observational cohort studies reporting subsequent treatment post-CDK4/6i progression in patients with HR+HER2-mBC from 2016 to December 2023. We performed a pooled analysis of Kaplan-Meier-derived individual patient data for progression-free survival (PFS) and overall survival (OS). Subgroups analysis according to drug type, and a sensitivity analysis including only RCTs were also conducted. Statistical analysis was performed with R Statistical Software. Results: Of 12,895 identified records, 18 studies (7 RCTs and 11 cohort studies) comprising 4,868 patients with HR+HER2-mBC were included. Maintaining treatment with a CDK4/6i post-CDK4/6i progression was associated with longer PFS (HR: 0.64; 95% CI: 0.54-0.76; p<0.01; n=1,397) and prolonged OS (HR: 0.70; 95% CI: 0.61-0.79; p<0.01; n=2,369) compared with ET monotherapy. The PFS benefit was seen in both continuing the prior CDK4/6i (HR 0.62; 95%CI: 0.54-0.72; p<0.01; n=1,178) or switching to a different CDK4/6i (HR 0.49; 95%CI: 0.30-0.82; p<0.01; n=638). Subsequent therapy with PI3K/AKT/mTOR inhibitors plus ET also achieved longer PFS (HR: 0.74; 95% CI: 0.61-0.90; p<0.01; n=744), but significantly shorter OS (HR 1.36; 95%CI: 1.09-1.71; p<0.01; n=1,564) compared with ET monotherapy. PFS with chemotherapy was not different from ET monotherapy (HR 0.93; 95%CI: 0.76-1.13; p=0.45; n=879) but exhibited shorter OS (HR 1.55; 95%CI: 1.38-1.72; p < 0.01; n=2,476). Sensitivity analyses including only RCTs, confirmed the greater PFS of maintaining CDK4/6i plus ET compared with ET monotherapy (HR: 0.69 95% CI: 0.57-0.83; p<0.01; n=751). Conclusions: This extensive data pool of RCTs and cohort studies suggests the potential clinical benefit of continued CDK4/6i after disease progression compared to ET monotherapy. Data from phase III trials will further aid in understanding this question. Our data also supports current guideline recommendations of ET-based therapies over chemotherapy as the preferred treatment sequencing in HR+ HER2- mBC.
Predicting CDK4/6 inhibitors outcomes in pts with HR+/HER2- metastatic breast cancer: A machine learning approach.
Authors: Moiso Enrico , Ferraro Emanuela , Cabel Luc , Safonov Anton , Ahmed Mehnaj , An Julia Ah-Reum , Jhaveri Komal L. , Norton Larry , Robson Mark E. , Modi Shanu , Chandarlapaty Sarat , Razavi Pedram
Published: June 2024

1074

Background: CDK4/6 inhibitors (CDK4/6i) in combination with endocrine therapy (ET) are the current standard of care for pts with newly diagnosed HR+/HER2- metastatic breast cancer (MBC). Although multiple pivotal trials showed a robust benefit of CDK4/6i over ET alone in all the subgroups, there is a subset of pts with a suboptimal response that is difficult to characterize. To predict the benefit on first line CDK4/6i in pts with HR+/HER2- MBC, we created a machine-learning (ML) model based on clinico-pathological features (CPFs) at baseline. Methods: We identified 854 consecutive pts with HR+/HER2- MBC receiving CDK4/6i as 1st line therapy between 12/2013 and 10/2023 from our MSK translational database. OncoCast-MPM ML framework was used to stratify pts based on progression-free survival (PFS) on 1st line CDK4/6i. CPFs of interest were selected as input for the models. Pts with missing data in any of the key inputs were excluded and used as hold out set. We tested 4 algorithms (GBM, ENET, LASSO and SVM), and selected the only model that returned predictions when tested on the hold out dataset containing missing data. The Kaplan-Meier estimator and the log-rank test were used to assess differences in PFS, and Cox regression was used to measure hazard ratios (HR) between groups. Results: Overall, 651 out of 854 pts and 15 CPFs were used in models' creation. The median PFS of the cohort was 15.95 months (95%CI: 14.04-17.95). Of the 4 tested architectures, GBM was the selected architecture based on its ability to be tested on the holdout cohort containing missing data. GBM identified 3 risk groups: good-response risk group (N=279), with a median PFS of 23.8 months (95%CI: 19.6-29.9), intermediate-response risk group (N=231), with a median PFS of 14.7 (I95%CI: 12.2-16.9), and poor-response risk group (N=141), with a median PFS 7.4 (95%CI: 5.3,9.1). The HR between good-response and poor-response RGs was 2.55 (95%CI: 2.0,3.2) with a of p = 2.54e-14. The first 5 CPFs by importance, sorted by Garson algorithm score are: disease-free interval, liver involvement, age at metastatic disease, adjuvant treatment-free interval, and progesterone receptor status. No statistically significant differences were observed between the 3 risk groups identified in the train-validation and tested in the holdout cohort, in terms of median, 1yr, 3yr survival times, as well as in HR. Conclusions: ML-based models have the potential to identify subsets of pts likely to poorly respond to first line CDK4/6i leveraging clinico-pathological features. Risk stratification can help clinicians to select pts who may benefit from short-term interval imaging and potential cfDNA monitoring, as well as to identify the right population to design clinical trials with escalating treatment approaches.
Genomic alterations in DNA damage response (DDR) genes in HR+/HER2- metastatic breast cancer (mBC) and impact on clinical efficacy with sacituzumab govitecan (SG): Biomarker results from TROPICS-02 study.
Authors: Bardia Aditya , Zhang Yi , Marmé Frederik , Schmid Peter , Cortes Javier , Tolaney Sara M. , Zhang Yajia , Yoon Oh Kyu , Verret Wendy , Das Thakur Meghna , Rugo Hope S.
Published: June 2024

1075

Background: In the phase 3 TROPiCS-02 study, SG, a Trop-2–directed antibody-drug conjugate coupled to SN-38 as the payload, demonstrated clinically meaningful improvement in survival outcomes over chemotherapy in patients (pts) with pretreated HR+/HER2- mBC. SN-38 leads to double-stranded DNA damage, therefore we hypothesized that in tumors with defective DDR machinery, SG may provoke synthetic lethality. We report on comprehensive genomic analysis of DDR gene variants and the impact on SG clinical efficacy in this patient population. Methods: Pts with HR+/HER2– mBC who received prior taxane, endocrine therapy (ET), CDK4/6 inhibitor, and 2-4 prior lines of chemotherapy were randomized to receive SG (10 mg/kg IV days 1 and 8, every 21 days) or treatment of physician’s choice (TPC) until disease progression or unacceptable toxicity. DDR gene deleterious variants were identified using whole exome sequencing (WES) on archival or screening tumor tissues based on 142 DDR pathway genes annotated in the Kyoto Encyclopedia Genes and Genomes (KEGG) database and Human DNA Repair Gene database; association between these variants and clinical outcomes was evaluated using Cox regression model as Hazard Ratio (HR) with 95% Confidence Intervals (CI). Results: Of 543 patients included in the intent-to-treat (ITT) population, WES data was available for 195 (36%) – clinicopathological features were similar between ITT and WES dataset (median age = 57 vs 58 for SG and 55 vs 55 for TPC; prior lines of chemotherapy >2 lines = 59% vs 57% for SG and 58% vs 55% for TPC). Estrogen Receptor (ER)>10% and prior lines of chemotherapy were comparable between WT and MUT in SG arm and in TPC arm. Overall, 114 (58%) of tumor samples had ≥1 deleterious alteration with BRCA2, PRKDC, ATM being the most common alterations. The primary results are included (Table). Although all patients demonstrated improved efficacy with SG vs TPC, patients with DDR mutant MBC had numerically greater benefit in PFS vs WT (MUT HR= 0.61; WT HR= 0.76) and OS (MUT HR = 0.68; WT HR= 0.82). Conclusions: While SG benefit over TPC was observed in both DDR WT and DDR MUT HR+/HER2– mBC, numerically greater benefit was observed for patients with DDR deficient tumors, suggesting possible synergy between the DDR pathway and SG’s anti-tumor effect. Further study of the synergistic effects of SG in combination with agents targeting DDR pathway are warranted. Clinical trial information: NCT03901339 . [Table: see text]
Exosomal HMGB1 educate PD-L1+-tumor associated macrophages via glycometabolic reprogramming to induce lung-tropic metastasis of triple negative breast cancer.
Authors: Chen Wei-xian , Zhu Bei , Cheng Tian-cheng , Wu Jia-hao , Zheng Lin
Published: June 2024

1090

Background: Lung metastasis occurs in one third of triple negative breast cancer (TNBC), the underlying molecular mechanism remains largely unclear. Mounting evidence suggests that PD-L1+-tumor associated macrophages (PD-L1+-TAMs) are closely associated with immune suppression, invasion, and metastasis. Tumor-derived exosomes have been reported to remodel tumor microenvironment and accelerate metastasis through packing and delivering a variety of biologically active molecules. The aim of this study was to investigate whether TNBC-derived exosomes were able to polarize lung macrophages towards PD-L1+-TAMs and promote a pre-metastatic immunosuppressive niche, therefore discovering the underlying mechanism of lung-tropic metastasis. Methods: Exosomes obtained from EO771 TNBC cell line (EO771/exo) and HC11 normal breast epithelial cell line (HC11/exo) were characterized. Absorption of exosomes by macrophages was observed by confocal microscopy. Mass spectrometry was used to identify the significantly highly expressed HMGB1 protein in EO771/exo, and ligands of HMGB1 on lung macrophages were detected by co-immunoprecipitation. Significance of EO771/exo and HMGB1 in inducing PD-L1+-TAMs and generating a pre-metastatic immunosuppressive niche were confirmed by both in vitro and in vivo studies. Functions of EO771/exo and HMGB1 on glycolysis and lactate production were evaluated by metabolism assays. Results: EO771/exo could polarize macrophages toward PD-L1+-TAMs and generate a pre-metastatic immunosuppressive niche. Mass spectrometry, clinical samples, and bioinformatics analysis showed that HMGB1 was significantly expressed in EO771/exo and was involved in cellular communication and metabolism processes. Co-immunoprecipitation and 3-dimensional modeling suggested a strong binding of HMGB1 with Tim-3 ligand on lung macrophages. Macrophages incubated with EO771/exo exhibited an enhanced glycolysis and lactate production. Flow cytometry demonstrated that green fluorescent protein (GFP)-EO771 tumor-bearing mice had more lung micro-metastases than brain and liver. Immunofluorescence and laser confocal microscopy demonstrated that EO771/exo were able to increase lung micro-metastases and escalate PD-L1 expression on lung macrophages. Moreover, elevated PD-L1+-TAMs and reduced CD3+CD8+ T lymphocytes were detected in TNBC positive axillary lymph nodes and lung metastasis specimens than TNBC negative axillary lymph nodes. Conclusions: Exosomal HMGB1 from TNBC could target Tim-3 ligand on lung macrophages and accelerate glycolysis and lactate production to induce PD-L1+-TAMs, thereby suppressing CD3+CD8+ T lymphocytes immunity and generating a pre-metastasis immune-suppressive niche. Our research would uncover a novel mechanism of lung-tropic metastasis.
Prevention of sacituzumab govitecan (SG)-related neutropenia and diarrhea in patients (pts) with triple-negative or HR+/HER2- advanced breast cancer (ABC; PRIMED): A phase 2 trial.
Authors: Pérez García José Manuel , Gión María , Ruiz-Borrego Manuel , Blancas Isabel , Lopez-Miranda Elena , Blanch Salvador , Recalde Sabela , Calvo Lourdes , Gonzalez Xavier , Ancizar Nerea , Morales Murillo Serafin , Cortez Patricia , Cardona Javier , Shimizu Eileen , Guerrero José Antonio , Sampayo-Cordero Miguel , Martinez-Bueno Alejandro , Cortes Javier , Llombart-Cussac Antonio
Published: June 2024

1101

Background: SG is a Trop-2 directed antibody-drug conjugate approved for pts with advanced, pretreated, triple-negative breast cancer (TNBC) and HR+/HER2- breast cancer. The most common SG-related adverse events (AEs) are neutropenia and diarrhea which can lead to treatment modifications. Granulocyte colony-stimulating factor (G-CSF) and loperamide (L) are frequently used for managing these AEs. PRIMED is assessing if primary prophylaxis with G-CSF and L can improve the tolerability of SG. Methods: PRIMED (NCT05520723) is an open-label, single-arm, phase II trial. Pts had received between 1-2 previous chemotherapy regimens for ABC, including a taxane in any setting, unless contraindicated. HR+/HER2- pts had to be endocrine-resistant. Pts received SG (10 mg/kg IV, d 1 and 8, every 21 d) until disease progression (PD) or unacceptable toxicity. G-CSF (0.5 MU/kg/day SC, d 3, 4, 10, and 11) and L (2 mg orally, twice a day or 4 mg QD, d 2, 3, 4, 9, 10, and 11) were given during the first two cycles. The primary endpoints were incidence of ≥ grade (G) 3 neutropenia (H0: ≥40%; H1: ≤22%) or ≥ G 2 diarrhea (H0: ≥25%; H1: ≤10%) after two cycles. Results: A total of 50 pts were enrolled between February 2023 and September 2023 (TNBC, n = 32 [64%]). At data cut-off on October 18, 2023 (median follow-up, 4.3 months), 31 pts remained on treatment. The main reason for treatment discontinuation was PD, which was reported for 16 pts. After the first two cycles, incidence of any G neutropenia and diarrhea were 28% and 34%, respectively. Eight pts (16%) had ≥ G 3 neutropenia, meeting this primary endpoint (p=0.0002). Eight pts (16%) had ≥ G 2 diarrhea (4% G 3), showing numerical benefit of prophylactic L (p=0.084). No pts developed febrile neutropenia. The overall rate of AEs associated with dose reductions and treatment interruptions was 18% and 44%, respectively. No treatment discontinuations due to AEs were reported. Conclusions: Prophylactic administration of G-CSF and L resulted in a clinically relevant reduction of the incidence and severity of SG-related neutropenia and diarrhea and limited AE related dose reductions/interruptions and treatment discontinuations. Clinical trial information: NCT05520723 .
Transcriptomic analysis of cAMP/PKA/CREB signaling in invasive lobular breast cancer.
Authors: Puthanmadhom Narayanan Susrutha , Wedn Abdalla , Shiraz Osama Shah , Chen Jian , Brown Daniel B , McAuliffe Priscilla F. , Lee Adrian V. , Oesterreich Steffi
Published: June 2024

1109

Background: Invasive lobular breast cancer (ILC) is the most common special type of breast cancer and has unique clinicopathological and molecular hallmarks that differentiate it from the more common invasive carcinoma – no special type (NST). Despite these differences, ILC and NST are treated as a single entity and there is a lack of ILC-targeted therapies. To fill this gap, we sought to identify novel molecular alterations in ILC that could be exploited for targeted therapies. Methods: Differential gene expression and Geneset Enrichment and Variation analyses were performed on RNA-seq data from three large public breast cancer databases – the Sweden Cancerome Analysis Network-Breast (SCAN-B; luminal A ILC N=263, luminal A NST N=1162), The Cancer Genome Atlas (TCGA; luminal A ILC N=157, luminal A NST N=307) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC; luminal A ILC N=65, luminal A NST N=533). Pathways enriched in overlapping differentially expressed genes from these datasets were clustered using Jaccard similarity to identify pathways enriched in ILC. The cAMP/PKA/CREB signaling was studied in ILC, ILC-like and NST cell lines and patient-derived organoids (PDOs) using forskolin, an activator of the pathway. Results: Clinicopathological features of patients with ILC and NST in SCAN-B were similar to prior population-based studies. There was a consistent pattern of up-regulation of cAMP/PKA/CREB related signaling in ILC compared to NST in SCAN-B, TCGA and METABRIC. Treatment with forskolin resulted in a greater increase in phospho-CREB in ILC cell lines and organoids than NST. CRISPR deletion of CDH1 in NST cell lines did not alter response of cells to forskolin as measured by phospho-CREB. Forskolin treatment caused growth inhibition in ILC and NST, with ILC cell lines being more sensitive to forskolin-mediated growth inhibition. Conclusions: In three separate datasets, cAMP/PKA/CREB signaling was identified to be higher in ILC than NST. This in silico finding was validated in cell line and organoid models. Loss of CDH1 was not sufficient to mediate this phenotype. Future studies should investigate the mechanisms for differential cAMP/PKA/CREB signaling and the potential for therapeutic targeting in patients with ILC.
Women’s insights on sexual health after breast cancer (WISH-BREAST).
Authors: Agrawal Laila , Teplinsky Eleonora , Feygin Yana , Kluthe Theresa , Menn Corinne
Published: June 2024

12132

Background: Sexual health is a prevalent and distressing toxicity in women after cancer treatment. Sexual health needs and treatment require multidisciplinary management and despite the existence of guidelines on the management of sexual health, are often overlooked in the clinical setting. Methods: An anonymous online survey regarding sexual health for people with a current or prior breast cancer diagnosis was distributed through a social media platform (Instagram) and e-mail. Questions included demographics, breast cancer history and treatment, sexual health symptoms, and experience with medical care for sexual health symptoms. Results: Out of 1775 respondents, 1462 answered the question of whether or not sexual health changed after breast cancer diagnosis or treatment & were included in this analysis. Mean age: 47.7 years. 87.3% of respondents identified as white and 1.6% as Black. Stage: 0 (8.5%), 1 (38.4%), 2 (34.2%), 3 (14.8%) & 4 (2.9%). Estrogen receptor positive (81.5%), HER2 positive (27%), triple negative (12.9%). Breast cancer diagnosis or treatments caused a moderate to great deal of change to sexual health in 89.5% of respondents and a moderate to great deal of distress in 85%. The sexual health concerns are summarized in the table. 73% of participants did not receive information about sexual health from their healthcare team. Among participants who reported a change to sexual health, only 12% were satisfied with how their sexual health concerns were addressed. Treatment was not offered for sexual health concerns to 39% of respondents and 63% had not been referred to any specialists for sexual health concerns. 46% of participants had not been offered non-hormonal treatments for genitourinary concerns, 55% were told vaginal hormones were not an option, and 83% were not offered treatment for low libido despite lower sexual desire. 80% of respondents received information about sexual health from social media. Of those, 62% stated that their primary source of information on social media were health care professional accounts. Conclusions: In this online survey, sexual health concerns were highly prevalent and distressing after breast cancer diagnosis. There was a very low level of discussion with medical professionals and treatments were infrequently offered to patients, despite the existence of medical guidelines on sexual health care for women after cancer. Patients are turning to social media, & specifically to medical professional accounts, for information. Future efforts to address sexual needs for breast cancer survivors and thrivers are warranted. [Table: see text]
Cost-utility of geriatric assessment (GA) in older adults with cancer: A model-based economic evaluation of four randomized controlled trials (RCTs).
Authors: Akseer Selai , Yeretzian Shant , Sahakyan Yeva , Abrahamyan Lusine , Puts Martine , Alibhai Shabbir M.H.
Published: June 2024

1509

Background: Geriatric assessment (GA) is a guideline-recommended approach to optimize cancer management in older adults undergoing chemotherapy. Our recent cost-utility analysis of the published 5C (Clinical and Cost-effectiveness of a Comprehensive geriatric assessment and management for Canadian elders with Cancer) RCT comparing GA and management (GAM) with usual care in older adults with cancer did not demonstrate cost-effectiveness overall. However, the trial was limited by <5% of study participants receiving GA prior to starting treatment. Three other GAM RCTs (GAIN, GAP-70, and INTEGERATE) have recently been published with evidence of efficacy on clinically relevant endpoints. Whether these are more cost effective than 5C is unclear. We evaluated the cost-effectiveness of GAM versus usual care in older adults with cancer using a decision model under a range of plausible scenarios representing the 4 trials. Methods: We performed cost-effectiveness analyses using the healthcare payer perspective and a 12-month time horizon. We incorporated Canadian costs and utility data from 5C, and used intervention details and effectiveness data from the three RCTs. We reported healthcare costs per quality-adjusted life year (QALY) and the incremental net monetary benefit (INMB) using a $50,000 per QALY threshold. In scenario analyses we examined the main cost drivers. Results: Across trials, the average QALY per patient ranged 0.577–0.662 for GA and 0.606–0.665 for UC, and the average total costs $31,234–$39,432 for GA and $29,261–$41,756 for UC. Chemotherapy expenses accounted for 46%-66% of total costs across trials. The INTEGERATE trial had a positive INMB of $6,074. The GAIN and GAP-70 trials had negative INMB value of -$2,123 and -$1,172, respectively. In comparison, in 5C, the total costs were $39,812 and $37,450 for GAM and UC, respectively, and QALYs were 0.728 and 0.751, respectively; the INMB was $-2,713. Conclusions: Trial results and the associated model of care from INTEGERATE suggested a positive net monetary benefit, primarily driven by reduced hospitalization. Evaluation of cost-effectiveness under a range of plausible scenarios from RCTs can provide important insights about GAM. Our results add to the growing data supporting the need to implement GAM in older adults with cancer starting chemotherapy and argue for its cost effectiveness under specific scenarios. Future trials should include hospitalization outcomes. Future economic analyses need to accurately capture chemotherapy costs.
Quality of life for older patients with metastatic cancer in Brazil: A telehealth-based geriatric assessment and supportive care intervention (GAIN-S).
Authors: Bergerot Cristiane Decat , Bergerot Paulo Gustavo , Razavi Marianne , Silva Jonas Ribeiro Gomes , Cerveira Jose Adolfo , Franca Marcos V S , Fuzita William Hiromi , Vasconcellos Vitor Fiorin de , Matos Neto Joao Nunes , Patriota Carolina Bezerra , Hada Aline Lury , Anjos Gabriel dos , Buso Murilo , Laloni Mariana , Ferreira Carlos G. M. , Nipp Ryan David , El-Jawahri Areej , Soto Pérez de Celis Enrique , Dale William
Published: June 2024

1514

Background: Older adults with cancer often present unique geriatric and supportive care needs. We sought to evaluate the impact of a telehealth-based multimodal geriatric assessment (GA)-guided supportive care interventions (GAIN-S) program among older patients with metastatic cancer in a Brazilian cancer center. Methods: This is a randomized trial. Patients aged 65+ years with metastatic cancer, undergoing treatment, regardless of ECOG status, were enrolled. Following the baseline assessment, patients were randomized 1:1 to receive usual care or GAIN-S. The GAIN-S intervention provided remote, telehealth-based consultations with a nutritionist, psychologist, psychiatrist, and certified fitness trainer. At baseline and 3-months, patients were assessed for emotional symptoms (Geriatric Depression Scale), functional status (Instrumental Activities of Daily Living), coping (BriefCope), and quality of life (Functional Assessment of Cancer Therapy-General). Independent t-tests and linear mixed model were used. Results: Out of 86 approached patients, 80 were enrolled (40 per arm), with 3 deceased during treatment (usual care: 2, GAIN-S: 1). Most patients were female (56%), with a median age of 73 years (range, 65-68). Most common cancers were genitourinary (28%) and breast (23%). At baseline, there were no differences in the outcome measures between arms. However, from baseline to 3-months, patients assigned to GAIN-S had improvements in emotional symptoms, functional status, and quality of life compared to usual care (Table). Additionally, those assigned to GAIN-S reported increased utilization of active coping, acceptance, and positive reframing at 3-months. Conclusions: GAIN-S demonstrated significant improvements in emotional well-being, functional status, and quality of life among older patients with metastatic cancer. These findings underscore the potential of such telehealth-driven approaches to enhance the supportive care experience in diverse healthcare settings. [Table: see text]
Medicaid expansion and cancer stage at diagnoses during the COVID-19 pandemic in the United States.
Authors: Han Xuesong , Yang Nuo Nova , Fan Qinjin , Nogueira Leticia M , Yabroff Robin
Published: June 2024

1526

Background: Substantial cancer underdiagnosis, especially for early-stage diseases, occurred during the COVID-19 pandemic in the US in 2020. The Affordable Care Act expanded Medicaid to nonelderly adults with income up to 138% Federal Poverty Level in states that opted in, potentially facilitating residents’ access to care during pandemic-related financial and employment instability, thus aiding in timely detection of cancer. This study examines the association of Medicaid expansion with changes in cancer stage at diagnosis during the COVID-19 pandemic. Methods: Adults aged 18-64 years newly diagnosed with cancer in 2019 and 2021 were identified from the National Cancer Database. Year 2020 was excluded to avoid confounding from distinct geographic patterns of COVID-19 infections. A difference-in-differences (DD) approach was used to compare the changes in proportions of patients diagnosed at stage I/II in 2021 vs 2019 between Medicaid expansion states and non-expansion states. Adjusted DD estimates were calculated with linear probability models and stratified by key sociodemographic factors and cancer type. Results: A total of 427,368 adults newly diagnosed with cancer in 2019 and 393,961 in 2021 were identified. Patients diagnosed with stage I/II decreased nationwide, however, decreases were larger in non-expansion states (from 58.3% in 2019 to 56.9% in 2021) compared to expansion states (61.4% in 2019 to 60.7% in 2021), leading to a DD of 0.92 percentage points in early-stage cancer diagnosis associated with Medicaid expansion (95% CI =0.46-1.38). The association was strongest among individuals aged 18-44 years (DD=1.46, 95% CI=0.42-2.49), men (DD=1.46, 95% CI=0.73-2.19), those living in most socioeconomically deprived areas (DD=1.40, 95% CI=0.41-2.40) and nonmetropolitan areas (DD=1.82, 95% CI=0.56-3.09). When stratified by cancer type, the largest associations were seen for esophageal cancer (DD=3.86, 95% CI=0.26-7.45) and prostate cancer (DD=2.81, 95% CI=1.43-4.18). Conclusions: Substantial cancer underdiagnosis and declines in proportion of early-stage diagnoses continued nationwide in 2021, the second year of the COVID-19 pandemic. However, the pattern was worse in non-expansion states, suggesting a protective effect of Medicaid expansion on cancer early diagnosis during the public health emergency. Findings may inform policy makers and the public in the 10 states that have yet to expand Medicaid eligibility.
Impact of age on clinical trial availability for AYAs with cancer: A time-trend analysis.
Authors: Sheth Bhutada Jessica , Mittal Nupur , Freyer David R. , Roth Michael
Published: June 2024

1534

Background: Low participation of adolescents and young adults (AYAs, age 15-39 yrs at diagnosis) in cancer clinical trials (CCT) limits their access to novel therapies and hinders the ability to study disease biology and age-specific toxicities. Patient age may be an important barrier as younger and older AYAs may be excluded depending on the trial’s focus. In 2017, the American Society of Clinical Oncology and Friends of Cancer Research issued a joint statement encouraging removal of age as a CCT eligibility criterion unless there is specific biological rationale. To evaluate the impact of this statement, we undertook this analysis of CCT availability for AYAs. Our primary objective was to compare the number of CCT available for AYAs, overall and by tumor types, from 2019-2023 vs previously published data from 2007-2018. The availability of early phase trials and study sponsor was also assessed. Methods: We identified CCT registered on ClinicalTrials.gov from January 2019 to July 2023 enrolling patients with 10 malignancies relevant for AYAs (Hodgkin lymphoma, anaplastic large cell lymphoma, melanoma, extracranial germ cell tumors [GCT], medulloblastoma, thyroid cancer, Ewing sarcoma, osteosarcoma, rhabdomyosarcoma [RMS], and synovial sarcoma). Trials were categorized as adult (≥18 yrs), transitional (patients < or ≥18 yrs), or pediatric (<18 yrs). Transitional trials with an age range 12-18 to <40 yrs were defined as AYA specific trials. Early phase included phase 1 and 1/2 trials; late phase included phase 2/3 and 3 trials. Trial availability from 2007-2018 was identified from a prior analysis by deRojas et al in 2019 (PMID:32337483). The proportion of trials in each category was compared between 2007-2018 and 2019-2023 using z-tests. Results: There were 1071 eligible trials registered on Clinicaltrials.gov: 840 (78%) adult, 226 (21%) transitional, and 5 (0.5%) pediatric. Four trials were AYA-specific. Compared to the prior 10 years, the proportion of transitional trials did not change overall (19% vs 21%, p=0.24) or within any disease. Whereas the proportion of trials available at age 17 has not significantly changed overall (20% vs 21%; p=0.48) or within any disease, the proportion of trials available at age 18 significantly increased (95% vs 98%; p<0.001) in aggregate and specifically for Ewing sarcoma (93% vs 100%; p=0.003), GCT (96% vs 99%; p=0.002), medulloblastoma (86% vs 98%; p=0.006), RMS (87% vs 98%; p=0.007) and thyroid cancer (92% vs 98%; p=0.01). Time trends for transitional trials by phase and sponsor are summarized (Table). Conclusions: Availability of transitional trials for AYAs has not increased, particularly for those <18 yrs. The 18-yr-old age limit continues to be an obstacle in CCT availability and enrollment. [Table: see text]
TriHealth Cancer Institute’s collaboration with the Tempus AI TIME program impact on clinical trial operations and enrollment.
Authors: Maher James F. , Mallahan Samantha , Claes Jason Joseph , Thompson Wayne , Kuritzky Benjamin , Neff Robert , Shatavi Seerin Viviane , Rice Courtney , Huelsman Karen M. , Budde Leanne S. , Adhami Faisal , Shulman Megan , Degele Meghan , Donovan Blathnaid , Skelly Danielle , Patnaude Emily , Clifford Christian , Darmofal Annie , Osterman Chelsea Kendall , Cooney Matthew M.
Published: June 2024

1553

Background: TriHealth Cancer Institute has the largest personalized medicine program serving Cincinnati. TriHealth’s EMR integration with Tempus AI TIME allows for patient screening using an AI powered software TApp that matches to a broad clinical trial portfolio. Each patient is followed using LINK portal and trials can be activated rapidly via TIME’s operational model. The goal of this collaboration is to increase TriHealth’s patients' access for clinical trials. Methods: The TApp is software utilizing subject data, trial eligibility criteria, and NLP models for AI matching to TIME studies. Unique TApp searches occur whenever there is new patient data or changes to eligibility criteria. All TApp matches are reviewed by Tempus AI nurses followed by confirmatory screening by TriHealth’s staff. Trials were activated using the TIME program’s standardized operational methods including a pre-negotiated rate card, trials agreement, and a central IRB. Data included number of patients screened, unique TApp searches, trial activations, consents, operational metrics, and financial impact. Results: From January 2022 - March 2023, TApp performed 8,653,397 unique searches for 135 TIME trials on TriHealth’s population of 18,823 patients. During this period, 985 trial eligibility criteria were modified and 200,776 patient clinical updates occurred. There were 2,032 potential matches (1,944 interventional, 88 observational) for 45 different trials. Tempus AI nurses spent 389 hours reviewing all 1,944 interventional matches and of these sent 284 to TriHealth for evaluation. For TIME studies, 28 patients consented (18 interventional, 10 observational) and 7 trials were activated (4 interventional, 3 observational). Total trial billable revenue for TIME studies was approximately $241,500 ($34,500 average per trial). Regarding non-TIME trials, 3 patients consented on 3 interventional studies. Activation time for non-TIME trials compared to TIME trials was 186 days versus 37 days. Conclusions: TriHealth’s partnership with TIME evaluated 18,800+ patients for 135 trials. Over 8.6M unique TApp searches resulted in 2,000+ patients screened by nurses. Operationally, TIME trials resulted in a 2.3X increase in the number of trial activations, an 80% reduction in days to activation, and 9.3 fold increase in enrollment compared to non-TIME studies. The use of AI enabled patient screening, combined with a structured trial activation process, improved patient enrollment at a community health system. [Table: see text]
A machine learning algorithm based on multi-omics biomarkers for the detection of tumor microsatellite instability.
Authors: Strickland Kyle C , Pabla Sarabjot , Wallen Zachary D , Nesline Mary K , Ko Heidi Chwan , Previs Rebecca A. , Conroy Jeffrey M , Sathyan Pratheesh , Saini Kamal S. , Jensen Taylor J. , Caveney Brian , Eisenberg Marcia , Ramkissoon Shakti H , Severson Eric A
Published: June 2024

1554

Background: Microsatellite instability (MSI) occurs via defects in mismatch repair (MMR) and is characterized by high tumor mutational burden (TMB) and a robust inflammatory response. Accurate MSI-high classification of immune-evasive tumors is vital due to the effectiveness of immune checkpoint inhibitor (ICI) therapy, such as pembrolizumab, which is FDA approved for all MSI-high tumors irrespective of anatomic origin. Detection methods of MSI-status vary widely, including immunohistochemistry (IHC), polymerase chain reaction (PCR), and next-generation sequencing (NGS). We developed a machine learning (ML) model to predict MSI status in patients with solid tumors using comprehensive genomic and immune profiling (CGIP), independent of direct sequencing data from microsatellite sites. Methods: We analyzed samples from 1,838 patients with colorectal cancer (CRC) by CGIP, which included DNA panel testing (523 genes) for pathogenic single nucleotide variants (pSNV) and determination of TMB (mut/Mb), and RNA sequencing (397 genes) for gene expression (GEX). The Boruta algorithm was used to select key genomic and GEX changes associated with MSI status. A distributed gradient boosting algorithm created a predictive model that was trained on 70% of the cohort. The model was tested on the remaining CRC cohort (Test), and in the PanCancer Atlas CRCs (TCGA), endometrial adenocarcinomas (EMCA), and CRC with indeterminate MSI testing by CGIP. Performance of the trained model was assessed using sensitivity, specificity, and positive (PPV) and negative (NPV) predictive value. Results: Feature selection identified 79 genes with pSNVs, 63 GEX changes, and TMB as informative for MSI prediction. The model showed high predictive accuracy in differentiating MSI-H tumors. Of the 39 cases that failed MSI component of CGIP (Indeterminate), 17 had MMR IHC results available, of which 1 demonstrated loss of MLH1/PMS2 and the other 16 showed intact (normal) expression. Testing of this cohort identified 3 cases as MSI-high, at least one of which was confirmed by IHC. No cases with intact MMR protein IHC were identified as MSI-high by the algorithm. Conclusions: Our ML-driven approach accurately assessed MSI status of CRC and EMCA using CGIP data. This approach also identified potential cases with MSI-high status where direct sequencing of microsatellites failed. This study highlights a method to identify patients with potential MSI-high status for orthogonal screening with the MSI component of a test fails. [Table: see text]
Efficient site selection for clinical trials using simulated annealing.
Authors: Ruchlin Ian , Govil Vibhor , Samar Deepak , Chawla Jitesh , Gurha Pyeush
Published: June 2024

1558

Background: Identifying sites with eligible patients for multi-site oncology clinical trials is challenging given increasingly complex inclusion/exclusion criteria, limited site resources, and the need to ensure diversity in trials. This is a complex systems problem with many factors that present nonlinear behaviors. Given manifold combinations of sites, research capabilities, and study characteristics, artificial intelligence solutions may help research sites and sponsors optimize site selection to achieve enrollment, speed, and diversity of goals. We report on one of the first deployments of a multi-AI model solution to optimize site selection for an ongoing clinical trial. Methods: The clinical trials were translated into a standardized digital form expressed as rules fully encompassing the inclusion and exclusion criteria. A patient cohort was created from the criteria using the ConcertAI oncology research database, including site affiliations. The sites had numerical features specific to the protocol indication, such as physician count and projected patient count. Each site was scored by its features with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to create higher alignment to the best matched sites. Feature weights allowed TOPSIS to emphasize desirable attributes in an interpretable way. A simulated annealing algorithm, adept with nonlinear objectives, explored site combinations, yielding a high-scoring, constraint satisfying solution. Independent simulations measured convergence and provided a distribution of solutions. Shapley analysis clarified site contributions to score and constraints. The implementation was compiled and parallelized. Results: Utilizing a Multiple Myeloma clinical trial protocol with 7 criteria, we formed a cohort of 15,881 patients across 1,246 US clinical trial sites. Each site had 12 features. The weights optimized patient diversity while enrolling at least 10 patients per month across all sites to achieve the targeted study accrual timeline. The result was a set of 3 sites enrolling 12 patients per month with 51% diversity, in agreement with the optimal solution obtained through detailed, multi-week, manual analysis. As constraints increased, and exact verification became impractical, convergence was gauged by decreasing variance in independent solutions. Conclusions: Our study introduced a robust, efficient, and interpretable approach to clinical trial site selection. It addressed the challenges posed by increasingly complicated protocols, requirements for study participant diversity, and heterogeneous site features. The multi-AI model scalability underscored its practical utility in streamlining the site selection process for clinical research networks, academic centers, industry sponsored trials, cooperative group studies, and investigator-initiated studies.
Large language models to evaluate racial discrepancies in performance status assignment.
Authors: Demirci Arda , Hong Julian C. , Zack Travis
Published: June 2024

1561

Background: Oncologic treatment eligibility relies heavily on “Performance Status” (PS), a subjective gauge of a patient's overall health. Despite frameworks aimed at quantifying PS, these assessments remain prone to potential bias. A systematic evaluation of discrepancies in language between ECOG PS and race has yet to be conducted. Large language models (LLMs) have the ability to synthesize text and may enable an assessment of the relationship between race, note text, and physician-documented PS. We hypothesize that LLMs can quantify these relationships to understand potential inconsistencies in ECOG PS. Methods: In our single-institution cohort study, we examined patients from medical or radiation oncology clinics between January 2012 to December 2023 with documented ECOG PS. PS was extracted from clinical notes and redacted from downstream analyses. Notes were categorized by patient-reported race (Asian, Black, White, Other). 1,500 matched subjective assessments (from oncologist clinical notes) and PS were randomly sampled for each race, except for Black patients, where only 640 entries were available. We divided training and test sets using an 80-20 ratio across each race. Using the training cohort, we trained race-specific models to assign ECOG PS based on subjective assessment, using two LLMs: UCSFBERT (BERT pretrained on UCSF data) and RoBERTa. In the hold-out test sets, we applied each model across all races to assign ECOG PS based on subjective assessments. These were evaluated by micro-F1 (model accuracy) and Multiway ANOVA to compute model-specific p-values. Results: 13.6% of patients had a documented ECOG 2+, with variation across races (Asian: 16.1%, Black: 17.7%, White: 7.7%, Other: 15.3%). Models tended to assign Black patients with ECOG 0-1 with worse performance status (ECOG 2+). Other than RoBERTa models trained on Asian and White cohorts, all models trained on a specific race showed disparate classification results when applied to other races (out-of-domain), highlighting potential biases in LLM models trained where a specific race predominates (Table; ANOVA). Conclusions: This study demonstrates a novel way to use LLM to assess discordance within physician documentation and performance status assignment. It underscores the need for incorporating diverse demographic data when using LLM in medical contexts. This research has potential to dissect how bias may be propagated within physician practice and provide insight into known disparities in clinical trial enrollment and standard of care implementation.[Table: see text]