bluuebunny/crossref_metadata_2025_split huggingface dataset:
Start low, go slow: A systematic review and meta-analysis of upfront tailored treatment dosing in older adults with advanced cancer.
Authors: Aleixo Gabriel , Ferrell William J. , Ani Julianne , Patel Tej A. , Parikh Ravi Bharat , Sedhom Ramy 
Published: May 2024

1625 Background: Older adults aged ≥65 with advanced cancer are underrepresented in treatment trials. This gap limits informed decision-making regarding the dose and tolerability of proposed therapies. Standard chemotherapy is associated with >50% serious adverse event rate among older adults, with frequent dose reduction and early treatment discontinuation. A "start low, go slow" (SLGS) approach begins systemic therapy at lower-than-standard doses and increases the dose if well-tolerated. This alternative dosing strategy has shown value in minimizing adverse events and functional decline without compromising the overall effectiveness of treatments. We conducted the first systematic review and meta-analysis of SLGS effectiveness among older adults across advanced cancers. Methods: This review, was registered with PROSPERO and adhered to PRISMA criteria, covering PubMed, Journal of Geriatric Oncology and EMBASE from January 2000 until December 15, 2024. Eligible study designs were randomized controlled trials, retrospective trials, and non-randomized clinical trials with patients with advanced cancers who underwent systemic therapy. We reported all studies that studied the SLGS approach. Our studied outcomes were overall survival (OS), progression-free survival (PFS), treatment discontinuation, and toxicity. Data extraction included author, patient, cancer type, treatment, and survival outcomes. A meta-analysis using fixed effects and risk ratios (RR) was performed when sufficient data was available; significant outcomes had α<0.05. Results: Our search identified 13 studies testing SLGS strategies in oncology, including 3,508 patients, with a median age 63-78 years. The -represented cancers included colorectal (6 studies, 3059 patients total), lung (2 studies, 113 pts), chronic myeloid leukemia (2 studies, 127 pts), non-Hodgkin lymphoma (1 study, 45 pts), and prostate (2 studies, 164 pts) cancers. Ten (77%) studies assessed OS and PFS. Five studies (39%) compared SLGS against standard doses, finding no significant differences in PFS and OS across all trials. Dose escalation rates for SLGS ranged from 5% to 60%. The ability to complete planned cycles was higher with SLGS compared to standard dose (1 study, 43% vs 26%, p=0.04). Treatment discontinuation was not different for SLGL vs. standard dose (5 studies, meta-analysis RR 1.07, 95% CI 0.90-1.27, p=0.42). Toxicity ranged from 5% to 89% across studies; SLGS had lower grade ≥3 adverse events compared to standard dose (4 studies, meta-analysis RR 0.88, 95% CI 0.80-0.94, p < 0.001). Conclusions: This is the first systematic review and meta-analysis analyzing the SLGS approach to systemic therapy dosing in older adults with advanced cancer. Compared to standard-dose systemic therapy, older adults pursuing a SLGS strategy had greater completion of planned cycles, reduced toxicity, and similar survival.
Prognostic value of Oncotype recurrence score (RS) and Mammaprint (MP) in premenopausal patients with hormone positive (HR+) breast cancer (BC) with low genomic risk, stratified by race: A study of the National Cancer Database (NCDB).
Authors: Sivapiragasam Abirami , Ashok Kumar Prashanth , Huang Danning , Wang Dongliang 
Published: May 2024

551 Background: It is hypothesized that in African American (AA) women, RS has a lower prognostic accuracy. We evaluated this with a large population based national database. Methods: The 2021 NCDB PUF was used to include premenopausal female BC patients aged 18-50 years. Inclusion criteria were N0, M0 patients with any T stage, RS ≤ 15 or MP low risk, estrogen or progesterone receptor+ and HER2-. Patients were stratified by their recorded race (Caucasians vs AA). Univariate analysis was used to study the distribution. Kaplan-Meier (KM) and multivariate (MV) propensity score (PS) weighted Cox model were used to compare survival between the cohorts. Results: 27523 patients had an RS≤15 [Caucasian-25227(91.66%) AA-2296(8.34%)] and 4818 had MP low [Caucasian-4393(91.18%) AA-425(8.82%)]. >99% had regional lymph node surgery and >90% of the patients did not get chemotherapy. >70% of the patients were T1. Majority did get hormonal therapy (HT) [RS≤15 Caucasian-92.97% AA-91.81%, MP low- Caucasian-92.42% AA-89.65%]. On analyzing grade, AA had more poorly differentiated tumors [RS≤15 Caucasian-6.18% AA-9.46% p=<0.001 MP low- Caucasian-9.1% AA-16.02% p=<0.001]. KM survival estimates for RS≤15 at 5 years [Caucasian-99.3(99.2,99.5) %, AA-98.8(98.0,99.3) %] were similar and 10 years [Caucasian-97.5(97.0,97.9) %, AA-94.6(91.6,96.6)] showed a small difference. For MP low, the survival at 5 years [Caucasian- 99.0(98.6,99.3) %, AA-98.9(97.0,99.6) %] and 10 years [Caucasian- 97.0(95.9,97.8) %, AA-95.8(91.0,98.1) %] were almost equal. Adjusted Hazard Ratio estimate for Caucasian vs AA for RS≤15 did not reach significance overall [0.802 (95% CI 0.47-1.37)] nor when stratified by grade, histology, or T stage. Conclusions: Through our analysis, we show that there was no major difference in overall survival between Caucasians and AA among low genomic risk, premenopausal, hormone positive, N0 BC patients. There was a 2.9% difference between the racial groups at 10 years, but this was not seen in the adjusted analysis. The results show that genomic scores like RS and MP retain their prognostic utility even in the low-risk spectrum in both Caucasians and AAs. These results differ from other database studies, where the utility of these tools in the low-risk AA groups were questionable. Confounding associated with retrospective studies could be contributing to this and the predictive ability of genomic scores in varied racial groups needs to be analyzed in prospective models.
Patient-derived tumor cell clusters (PTC) guiding-neoadjuvant therapy of HER2-positive breast cancer: A prospective randomized phase II clinical trial.
Authors: Yu Xingfei , Wu Xiaofan , Wang Chen , Feng Weiliang , Zheng Yabing , Yang Hongjian 
Published: May 2024

581 Background: In a previous study, the patient-derived tumor-like cell clusters (PTC) were confirmed to be an accurate medicine effect-predicting model in vitro for clinical practice (1). We designed this prospective randomized phase II trial to research if this PTC-guiding strategy could improve the effect of neoadjuvant therapy in human epidermal growth factor receptor 2 (HER2) positive breast cancer (NCT05103293). Methods: We enrolled HER2-positive early breast cancer patients planning for neoadjuvant therapy to accept the PTC-guiding regimen as an experimental group or regimens of the physician's choice as a control group randomly. All eligible patients in the experimental group would receive medicine-sensitive testing by PTC then accepted the regimen with the highest PTC killing rate (30% as the lowest cut-off value) from the three candidate regimens (Cyclophosphamide combined with epirubicin -- Docetaxel combined with trastuzumab and pertuzumab, EC-THP, Docetaxel and carboplatin with trastuzumab and pertuzumab, TCbHP and Docetaxel with trastuzumab and pyrotinib, THPy). The primary endpoint is pathological complete response (pCR) in two groups using superiority odd ratio Fisher's exact test (one-sided alpha =0.05, power of 80%, and superiority margin at 0.1). The secondary endpoints are Miller-Payne (MP) grade 4~5 proportion, objective response rate (ORR), disease-free survival (DFS), and overall survival (OS). Results: Finally, 86 patients were enrolled in this study, 44 in the experimental and 42 in the control groups. The experimental group had 65.9% of pCR, significantly higher than 42.9% in the control group (Hazard ratio=0.388, P=0.033). The PTC-guiding treatment also considerably increased MP 4~5 proportion (79.5% vs. 59.4%, Hazard ratio=0.283, P=0.009) and objective response rate (90.9% vs 71.4%, Hazard ratio=0.250, P=0.027). After a two-year medium follow-up, the disease-free survival of the PTC-guiding treatment group was 84.1% higher than 71.4% of the control group without a significant difference (Log Rank, P=0.106). The two groups had similar overall survival (Log Rank, P=0.958). Furthermore, the PTC-guiding strategy significantly impacted pCR in univariate and multivariate regression analyses but not survival. Conclusions: In this trial, we concluded that the PTC-guiding neoadjuvant therapy could improve the effect, including pCR, MP score, and ORR in HER2-positive breast cancer. 1. Yin et al., Sci.Transl. 2020. Clinical trial information: NCT05103293 .
Prediction of pCR with pretreatment MRI radiomics in triple negative breast cancer treated with neoadjuvant chemo-immunotherapy.
Authors: Ramtohul Toulsie , Lepagnay Victoire , Bonneau Claire , Jin Maxime , Menet Emmanuelle , Sauge Juliette , Laas Enora , Romano Emanuela , Bello Diana , Mechta-Grigoriou Fatima , Bidard Francois Clement , Langer Adriana , Malhaire Caroline , Cabel Luc , Tardivon Anne 
Published: May 2024

589 Background: Neoadjuvant chemo-immunotherapy (NACI) has become the new standard of care for stage II-III triple-negative breast cancers (TNBC). This approach is linked to high rates of pathological complete responses (pCR), yet factors influencing responses to this regimen remain poorly characterized. Our objective was to investigate whether pretreatment MRI perfusion-based radiomics could serve as a predictive tool for pCR to NACI in patients with TNBC. Methods: This prospective study enrolled women with early-stage TNBC undergoing NACI at two different centers from August 2021 to July 2023. Tumor segmentation and pharmacokinetic analyses of pretreatment multi-vendor dynamic-contrast-enhanced (DCE)-MRI were conducted using the standard perfusion Tofts model. Radiomics features were extracted from the Ktrans, Ve, and Slopemax maps. Unsupervised correlation analysis of reproducible features and least absolute shrinkage and selector operation were employed to construct a radiomics score. The performance of the radiomic score was evaluated using the area under the receiver operating characteristic curve (AUC). A multivariable logistic regression model was employed to establish a multimodal nomogram. Performance metrics included discrimination, calibration, and clinical usefulness, assessed on the external validation set. Results: The training set comprised 112 patients from center 1 (mean age, 52 years ± 11 [SD]), and the external validation set included 83 participants from center 2 (mean age, 49 years ± 11 [SD]). Overall, the pCR rate was 70% (137/195). In the validation set, the radiomic score achieved an AUC of 0.80 (95% CI: 0.70, 0.89) for predicting pCR. A nomogram incorporating the radiomics score, tumor grade, and Ki67 yielded an AUC of 0.86 (95% CI: 0.78, 0.94) and demonstrated superior predictive efficacy compared to the histological prediction model (AUC, 0.76 [95% CI: 0.66, 0.87]; P = .02) in the validation set. Calibration curves of the nomogram exhibited good concordance between predicted and observed pCR in both sets. The radiomic score correlated with tumor size, washout enhancement curve, androgen receptor (AR), and combined positive score (CPS) PD-L1 levels (all P < 0.05). Conclusions: PretreatmentMRI-based radiomics is a reliable predictor of pCR to NACI and might help customizing treatment choice for early-stage TNBC patients.
Pathological complete response (pCR) association with a novel homologous recombination deficiency HRD signature (HRDsig) in patients with triple-negative breast cancer (TNBC) receiving neoadjuvant therapy (Tx).
Authors: Gupta Tanya , Graf Ryon P , Schrock Alexa B. , Madison Russell , Ross Jeffrey S. , Levy Mia Alyce , Quintanilha Julia 
Published: May 2024

591 Background: The current standard of care for stage II-III TNBC is neoadjuvant Tx combining carboplatin, paclitaxel, and immune checkpoint inhibitor (ICI) followed by doxorubicin and cyclophosphamide (AC) + ICI. This regimen is often associated with significant toxicity. This study aimed to investigate if HRDsig could identify patients with TNBC who have a greater benefit from the addition of platinum in the neoadjuvant Tx regimen. Methods: This study included patients with TNBC who underwent genomic testing using Foundation Medicine tissue comprehensive genomic profiling (CGP) assays and had records of neoadjuvant Tx. Patient clinical data was obtained by the US-wide de-identified Flatiron Health and Foundation Medicine real-world clinicogenomic breast cancer database (CGDB), originated from ~280 US cancer clinics between January 2011 and June 2023. pCR rates were compared between patients HRDsig(+) vs. HRDsig(-) who were stratified by having received platinum vs. non-platinum Tx and between patients receiving non-platinum vs. platinum neoadjuvant Tx stratified by HRDsig status. The interaction effect of HRDsig and platinum Tx in relation to pCR was evaluated by logistic regression. Results: 497 patients met the inclusion criteria, 159 (32%) with HRDsig(+) and 338 (68%) with HRDsig(-). Among HRDsig(+) patients, 54 (34%) received platinum and 105 (66%) non-platinum Tx. HRDsig(+) vs. HRDsig(-) patients were more likely to have pCR receiving both platinum Tx (37.0% vs. 4.4%, p<0.001) and non-platinum Tx (23.8% vs. 5.2%, p<0.001). Platinum vs. non-platinum Tx showed a trend towards moderately enriched pCR rates in the HRDsig(+) group (37.0% vs. 23.8%, odds ratio [OR]=1.87, 95% confidence interval [CI] 0.97-3.84, p=0.08), but not in the HRDsig(-) group (4.5% vs. 5.2%, OR=0.86, 95% CI 0.23-2.55, p=0.767). HRDsig(+) was independently associated with pCR (OR=5.65, 95% CI 2.80-11.89, p<0.001), while platinum Tx and pCR were not associated (OR=0.84, 95% CI 0.23-2.45, p=0.767). A strong treatment interaction between HRDsig status and platinum Tx was not observed (p=0.242, OR=2.24, 95% CI 0.61-9.58). Conclusions: In the neoadjuvant Tx setting, patients with TNBC that were HRDsig(+) were substantially more likely to achieve a pCR. There was a trend towards higher pCR rates among HRDsig(+) patients receiving platinum vs. non-platinum Tx, while this effect was not observed among HRDsig(-) patients. TNBC patients (especially stage II) often experience significant toxicity from chemotherapy regimens. These hypothesis-generating results suggest that HRDsig may help identify patients who achieve additional benefit from platinum agents. These results warrant further evaluation in randomized cohorts to potentially validate this utility.
Effect of a novel artificial intelligence (AI) –enabled multi-trial matching system on patient matching using real-world data.
Authors: Kurnaz Selin , Loaiza-Bonilla Arturo , Carvallo Castañeda Darla , Huner Oz , Giritlioglu Dersu ,   Precision Cancer Consortium
Published: May 2024

e13501 Background: Currently clinical research teams at sites are manually matching patients to clinical trials, where each trial in our experience takes at least 25 minutes using highly trained dedicated resources. This limits cancer patients’ clinical trial options and enrollment rates. Moreover, the lack of NGS testing results may also negatively impact matching to clinical trials in targeted therapies. PCC, a consortium of 7 of the Top 20 Pharmaceutical companies, collaborated with Massive Bio to demonstrate how cancer patients’ matching rates can be increased if patients are prescreened to multiple trials simultaneously (i.e. multi-trial matching) instead of a single trial and NGS testing results are integrated into the matching process. Methods: Massive Bio has developed a first-in-class AI-enabled matching system to extract 180 structured clinical data from medical records using computer vision and natural language processing and a recommendation system for matching patients to parameterized inclusion/exclusion (I/E) criteria from over 14,000 actively recruiting interventional clinical trials.Our analysis included a sample of 5,707 cancer patients from the Massive Bio Synergy AI real-world database, corresponding to tumor types in 23 selected trials. We developed a decision-tree algorithm for retrospective matching analysis using modeled I/E criteria and compared these results to the theoretical matching rate (TMR) for each trial based on tumor type and biomarker prevalence, extent of disease at diagnosis and prior treatment history. Results: 690 patients matched to at least one trial were matched to 1.82 times more trials in multi-trial matching; 2.10 times more potential matches were obtained with hypothetical 100% NGS testing; and 99.9% matching time was reduced with AI enabled system; key findings are summarized (Table). Conclusions: This study confirms the underutilization of NGS technology and substantial benefits of AI and NGS in cancer trial matching. Their use resulted in a nearly two-fold increase in potential patient eligibility for trials, and an unprecedented reduction in manual effort, underscoring a significant advancement in the efficiency of the clinical trial matching process. A prospective country-wide analysis is under consideration.[Table: see text]
NGS panels' capture of biomarkers associated with targeted therapies in clinical trials.
Authors: Fox John Leonard , Daniel Sugganth , Abrol Manavi 
Published: May 2024

e13508 Background: ASCO and NCCN guidelines strongly encourage participation in clinical trials though participation rates remain low. Although up to 60% of trials require biomarker information as a prerequisite to participation, guidelines are silent on biomarker testing to assess eligibility. To help inform policy development, we analyzed commercially available NGS panels to assess the capture rate of the specific gene variants required for targeted therapies in clinical trials. Methods: Publicly available gene variant information on 12 high volume NGS tissue and plasma commercial assays representative of panel size was accessed. The JAX-CKB database was queried to identify genomic prerequisites in active phase I-III clinical trials; mRNA and protein expression biomarkers were excluded. We used unpaired t-testing to compare the ability of large versus small panels to detect variants required for targeted treatments. (Somatic gene variant annotations and related content have been powered by The Jackson Laboratory Clinical Knowledgebase (JAX-CKBTM)). Results: Overall, 185 genes were linked to eligibility for targeted therapies in clinical trials (Table). Large panel assays (>80 genes) had a higher average capture rate compared to smaller panels, (84% vs. 46%, p value < 0.000002). Similarly, capture rates in select cancers were higher in larger panels: lung (85% vs 59%), breast (92% vs 54%), prostate (86% vs 34%), pancreatic (84% vs 54%), colorectal (88% vs 52%). All results were statistically significant (p < 0.05). Smaller panels were more likely to exclude large genes (e.g. BRCA), genome-wide signatures (e.g. TMB), fusions, and copy number variants. Conclusions: NGS-based panels with more than 80 genes had higher capture rates for biomarkers required for clinical trials of targeted therapies. Clinicians searching for all relevant treatment options for patients should include large genomic sequencing panels to maximize identification of potential clinical trial eligibility. Professional societies and policy makers interested in enhancing clinical trial enrollment rates should consider the panel size-related variability in capture rates of genetic variants when developing recommendations. [Table: see text]
Disparities in access to antineoplastic immunotherapy and outcomes by insurance status: A nationwide analysis.
Authors: Javaid Saad , Frasier Kelly , Li Vivian , Vinagolu-Baur Julia , Ortega Yaguachi Nataly , Rodriguez Evadne , Del Castillo Olivia , Batista Raquel , Jonas Kenlee , Palma Laura 
Published: May 2024

e13523 Background: Immunotherapy has emerged as a pivotal component in the treatment of cancer, particularly owing to the progress made in targeted therapies. Our analysis aimed to quantify the disparities in access to immunotherapy and the associated outcomes. Methods: We used National Inpatient Sample data (2017-2020) to identify patients hospitalized with a primary diagnosis of antineoplastic immunotherapy, stratifying them by either Medicaid or private insurance. The aim was to determine disparities in the likelihood of immunotherapy across various demographic factors and differences in outcomes, such as mortality and healthcare resource utilization. Results: A total of 14,530 patients were hospitalized for antineoplastic immunotherapy, with 2,960 (20%) having Medicaid insurance and 7,760 (53%) having private insurance. Patients with Medicaid were younger than those with private insurance (17.22% vs 38.53%). Compared to Medicare, patients with private insurance were more likely to undergo immunotherapy (OR=2.65(2.31-3.04); p<0.001), while those with Medicaid had decreased odds (OR=0.75(0.61-0.92); p=0.007). Older patients were less likely to undergo immunotherapy than younger patients (36-45: OR=0.69(0.56-0.85), p=0.001; 46-64: OR=0.7(0.59-0.82), p<0.001; >65: OR=0.48(0.4-0.59), p<0.001). Compared to the White population, Hispanics (OR=1.3(1.12-1.51); p<0.001) and patients of other races (OR=3.33(2.86-3.88); p<0.001) had increased odds of undergoing immunotherapy, while Black patients had decreased odds (OR=0.43(0.35-0.53); p<0.001).The individuals with the highest median income were found to have the highest likelihood of undergoing immunotherapy (>$86,000, OR=2.23(1.92-2.59); p<0.001), followed by those in the less income groups ($65,000-$85,999: OR=1.6(1.38-1.86), p<0.001; $50,000-$64,999: OR=1.48(1.28-1.73), p<0.001). Patients in medium-sized (OR=1.27(1.03-1.55); p=0.022) and large (OR=3.49(2.93-4.15); p<0.001) hospitals were more likely to receive immunotherapy compared to those in small hospitals. Patients with Medicaid had a higher total hospitalization cost than those with private insurances (+$219,484(83,731-355,238); p=0.002). There was no observed difference in mortality rates among patients with Medicaid or private insurance who received immunotherapy (Medicaid: OR=0.86(0.1-6.98), p=0.88; Private: OR=0.67(0.11-3.96), p=0.66). Conclusions: The utilization of immunotherapy among Medicaid patients is found to be lower when compared to those with private insurance and Medicare. This disparity is also related to a higher overall cost of hospitalization in Medicaid patients. However, there was no difference in mortality between the different insurance types who received immunotherapy.