bluuebunny/crossref_metadata_2025_split huggingface dataset:
Coping with inter-observer variability when assessing AI for scoring of HER2-stained whole slides.
Authors: Thomas Florian , Pommeret Denys , Guinaudeau Emmanuelle , Poulet Bruno , Salhi Yahia , Chetritt Jérôme 
Published: June 2024

e12571 Background: Around 15% of breast carcinomas exhibit Human Epidermal growth factor receptor 2 (HER2) overexpression due to gene amplification. HER2 protein levels are assessed by Immunohistochemistry (IHC) with 4 scores (0, 1+, 2+, 3+). Only score 3+ (IHC) cases and score 2+ (IHC) with proven HER2 gene amplification are eligible for targeted anti-HER2 therapies; others are HER2-negative. However, tumors with score 1+ and 2+ not amplified could benefit from treatment with the new HER2-based antibody-drug conjugates, requiring an accurate HER2 scoring, which is challenged by interobserver variability. This drawback is challenging for AI-based HER2 scoring assessment, and it is thus important to understand this inter-variability and then be able to propose a probabilistic framework which quantifies and explains the discrepancy between the AI analysis and the pathologist scoring. Methods: We introduce a novel probabilistic framework designed to assign probabilities to scores generated by AI algorithms. To the best of our knowledge, this represents the pioneering effort to quantify the uncertainty surrounding AI predictive models for HER2 scores. The methodology relies on a high-dimensional multivariate Gaussian approximation of the HER2 scoring process, hinting on the precise identification of marked cells to a specified category based on membrane completeness and staining intensity. Introducing uncertainty in the categorical identification enables the quantification of uncertainty in the overall AI-scoring at the whole slide image (WSI) level. Consequently, instead of offering a singular score, we can allocate a probability of belonging to a particular category (0, 1+, 2+, or 3+) for the global score. This approach enables a comparison of the predicted likelihood with the distribution of scores among pathologists, rather than relying on a "hypothetical" ground truth, often determined by a majority-voting which can be noise-sensitive or which excludes ambiguous cases when an agreement is hard to reach. Results: For illustration, we use the Kwant HER2 algorithm developed by DiaDeep on a validation set of 68 HER2 cases, previously scored by three expert pathologists. The framework allows us to understand the discrepancy between pathologists as we introduce nuance to the AI scoring and underlines narrow probability margins in borderline cases, therefore depicting the inherent challenge for pathologists to draw a clear demarcation between closely aligned scores categories. Conclusions: The proposed framework underscores the intrinsic variability of HER2 scoring between pathologists and allows to analyze the AI predictions for HER2 scoring with more nuance, consequently enabling a more critical analysis of the results compared to a singular raw output. As we enter a new era of AI-assisted diagnosis, such a method could improve the way of assessing new AI tools and help interpret their results.
SE-GAP-ResNet: A machine learning model for abnormal breast detection.
Authors: Gorriz Saez Juan Manuel , Wang Shuihua , Zhang Yudong 
Published: June 2024

e12579 Background: Breast cancer is the most common cancer in women worldwide. Although screening has improved early-stage detection, challenges like high false positives and heavy workloads for radiologists persist, emphasizing the importance of early identification of breast irregularities, including masses and micro-calcifications. Methods: We use a subset of the mini-MIAS dataset, randomly choosing 100 abnormal and 100 healthy images, with abnormal images categorized into six sub-types. Preprocessing involves removing noises and excluding background and muscle regions. Our classifier is the ResNet-34 model, a deep convolutional neural network with 34 layers, known for effective pattern identification in medical images. Enhancements include: (1) The Squeeze-and-Excitation (SE) block boosts neural network discriminative power by dynamically recalibrating channel or feature importance. Integrated into ResNet-34, it forms the backbone network, enhancing the identification of relevant patterns for improved diagnostic accuracy. (2) Complex patterns at the system's output are condensed into a common disease pattern through global average pooling (GAP). This reduces model parameters, enhances interpretability, and facilitates the extraction of essential diagnostic information from the entire image. (3) Feature vectors from different layers are concatenated to merge low-level and high-level features. Low-level features encompass fundamental visual attributes such as pixel intensity and texture, while high-level features involve more complex patterns and structures, including organ shapes and anomalies. (4) We employ multiple-way data augmentation techniques to augment the training set, including rotation, translation, scaling, Gamma correction, and shear. The resultant model is referred to as SE-GAP-ResNet. Results: After 10 iterations of 10-fold cross-validation, SE-GAP-ResNet exhibited notable performance with a sensitivity of 95.60%, specificity of 93.30%, precision of 93.49%, accuracy of 94.45%, and an F1 score of 94.51%. Outperforming three state-of-the-art approaches, as shown in the table, two-sample t-tests confirm that SE-GAP-ResNet achieves significantly superior performance (p<0.05). Conclusions: SE-GAP-ResNet excels in identifying breast abnormalities. We aim to enhance the AI system by adding a multi-class diagnosis framework and the capability to predict lesion regions, with the goal of substantially reducing callback rates for abnormal breast diagnoses and improving diagnostic accuracy and efficiency. [Table: see text]
Predicting peripheral neuropathy following neoadjuvant therapy in patients with breast cancer.
Authors: Feiger Bradley , Biancalana Matthew , Shelton Amy , Blenman Kim , Lustberg Maryam B. 
Published: June 2024

e12639 Background: Administration of neoadjuvant chemotherapy (NACT) or radiation is widely used to improve outcomes in patients with breast cancer. This strategy has demonstrated remarkable efficacy in reducing tumor burden and increasing the likelihood of breast-conserving surgery. However, neoadjuvant therapy can induce peripheral neuropathy, a condition characterized by nerve damage or dysfunction in the extremities that often manifests as pain, tingling, or weakness in the hands and feet. The exact mechanism remains unclear, although likely involves the cumulative toxic effects of therapy on peripheral nerves. Treatment-induced neuropathy poses a substantial unaddressed challenge that can significantly impact the patient’s quality of life. Therefore, predicting and ameliorating neuropathy are crucial aspects of comprehensive cancer care. Methods: We used an AI spatial biology platform to create and assess 3D depictions of a cohort of breast cancer patients based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data. Clinical, pathological, and radiological data were collected on 74 patients from Yale New Haven Hospital. Due to missing regimen data, the final dataset included 71 patients, with mean age 51.1 (14.5) years. An AI-based segmentation algorithm was successfully employed on 63 patients, of whom 13 had neuropathy following NACT. Vascular and microvascular (MV/V) kinetic parameters were computed for each, and radiomic features were extracted. Machine learning models were developed for clinical features, MV/V features, and the combined set of features. All models were tested with leave-one-out cross-validation. Results: The clinical model did not forecast neuropathy in any patient, indicating poor predictive ability. The MV/V model performed the best, with accuracy, precision, recall, and AUROC of 0.84, 1.0, 0.18, and 0.69, respectively. The combined model showed intermediate performance, with accuracy, precision, recall, and AUROC of 0.81, 0.5, 0.18, and 0.58, respectively. The patient population limits broad conclusions, but suggests features that are aligned with increased occurrence of neuropathy. In particular, vascular features that describe transfer of nutrients between tissues, as well as the density of blood vessels within and around the tumor, are prominent within both the MV/V and combined models. Conclusions: These results indicate that features associated with the degree of proximal and intratumoral vascularity may be predictive of peripheral neuropathy in breast cancer patients. Moreover, these features can be extracted from standard-of-care DCE-MRI data. Expansion of this vascular analysis could enable physicians to better plan and manage care for patients by tailoring treatment dose. [Table: see text]
The effects of anlotinib combined with chemotherapy following progression on cyclin-dependent kinase 4/6 inhibitor in hormone receptor-positive metastatic breast cancer.
Authors: Xu Ting , Zhang Lili , Yuan Yuan , Hu Sainan , Dong Min , Xu Xinyu , Huang Jiayuan , Xiong Weili , Lou Kexin 
Published: June 2024

e13052 Background: Endocrine therapy combined with cyclin-dependent kinase (CDK) 4/6 inhibitors (CDK4/6i) is the preferred treatment for hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2–) metastatic breast cancer (MBC). However, there are currently no recommendations for therapeutic strategies after progression on CDK4/6i-based treatment. This study aimed to examine the efficacy and safety of anlotinib plus chemotherapy in HR+/HER2-MBC after progression on CDK4/6 inhibitors. Methods: We collected data from 32 patients with HR+/HER2– MBC treated with anlotinib plus chemotherapy after progressing on CDK4/6i at Jiangsu Cancer Hospital from March 2020 to October 2023. The median follow-up was 9.1 months (range, 2.0-19.7 months) as of the data cutoff date in October 2023. The primary endpoint was median progression-free survival (PFS), secondary endpoints included objective response rate (ORR), disease control rate (DCR), and adverse events. Results: The median PFS (mPFS) of all patients was 7.6 months [95% confidence interval (CI), 5.75-9.45]. There was no significant difference in mPFS between patients who responded to prior CDK4/6i treatment and those who did not. (8.3 months versus 6.8 months, p = 0.580). Besides, the ORR was 34.4% and DCR was 93.8%. The most frequently observed adverse events were anemia (50.0%), neutropenia (40.6%), thrombocytopenia (34.4%), and epistaxis (34.4%). Dose interruption or reductions due to adverse events occurred in 2(6.3%) and 5 (15.6%) patients, respectively. Conclusions: The study preliminarily demonstrates that anlotinib combined with chemotherapy may be an optional recommendation for patients with HR+/HER2- metastatic breast cancer who have progressed after CDK4/6i.
Effect of timing of recurrence on outcomes in patients with metastatic breast cancer treated with CDK4/6 inhibitors.
Authors: Niraula Sujan , Villamarin Diego , Smith Tae , Babbra Ramandeep , Mahant Akhil , Strawderman Myla S. , Kharel Zeni , Tinkham Christie , Tiongson Michael , Bamarajpet Nikhil , Houshyar Samin , Kim Erica , Weiss Anna , Falkson Carla Isadora , O'Regan Ruth , Zhang Huina , Dhakal Ajay 
Published: June 2024

e13067 Background: CDK4/6 inhibitors (CDKi) + endocrine therapy (ET) comprise the standard 1st line treatment for ER+ HER2- metastatic breast cancer (MBC). However, there is a gap in understanding how timing of MBC recurrence affects clinical outcomes on CDKi. We conducted a study to compare clinical outcomes of MBC patients on CDKi based on timing of MBC recurrence. Methods: This retrospective study enrolled ER+ HER2- MBC patients diagnosed from Jan 2015 to Jan 2023, who received CDKi + ET as 1st line treatment for MBC. Patients were categorized as de novo MBC (dMBC), if they had 1. Stage 4 disease at initial diagnosis or 2. MBC diagnosed < 6 months of the primary breast cancer (PBC) diagnosis and before starting any systemic treatment for PBC. Patients with distant recurrence occurring < 5 years, 5-10 years, and >10 years from PBC were categorized as early, intermediate, and late MBCs (eMBC, iMBC, laMBC). Endpoints were Progression-Free Survival (PFS) and Overall Survival (OS) from MBC diagnosis. Baseline variables were compared using t-tests (continuous) and Chi-square tests (categorical). Endpoint analyses were conducted using Kaplan-Meier method and compared using Log rank test. Multivariate analyses were performed using Cox models. Results: Out of 280 patients enrolled, 67 were dMBC, 75 eMBC, 56 iMBC, and 82 laMBC. The laMBC group had a higher mean age (years) compared to other groups (71 vs. 62 in dMBC+ eMBC + iMBC, p<0.001). 64.5% of laMBC had visceral disease compared to 50.5% of dMBC + eMBC + iMBC (p=0.031). 65.7% of dMBC patients were treated with palbociclib compared to 80.8% of eMBC + iMBC + laMBC (p=0.010). Higher % of eMBC were PR- vs other cohorts (41.3 vs 23.9 dMBC + iMBC + laMBC, p<0.001). Among the 3 non dMBC groups, prior ET sensitivity (no recurrence for 2 years on adjuvant ET) was lower in eMBC (45.3%) compared to iMBC + laMBC (81.9%, p<0.001). 61.3% of eMBC patients were on adjuvant ET at recurrence compared to 17.4% of iMBC + laMBC (p<0.001). Other variables were similar. Table shows unadjusted endpoint analyses. In multivariate analyses, the risk of PFS events were not significantly different among cohorts (age<=65, ECOG performance status (PS) >=2 and PR- were independently associated with shorter PFS); risk of death was higher in eMBC vs laMBC (HR 1.73, p=0.047). Conclusions: In this retrospective study of ER+ HER2- MBC patients treated with 1st line CDKi + ET, timing of MBC recurrence was not associated with PFS differences after adjusting for other variables. However, patients with MBC recurring < 5 years of PBC had the higher likelihood of death compared to those recurring >10 years of PBC. [Table: see text]
The association of hormone receptor expression level and clinical efficacy of CDK4/6 inhibitor in hormone receptor-positive, HER2-negative metastatic breast cancer.
Authors: Bao Kelvin K. H. , Wong Carol HY , Yung Jackie , Tam Venus , Cheung Ka Man , Chan Jeffrey CH , Yiu Harry HY 
Published: June 2024

e13069 Background: In patients with hormone receptor-positive, HER2-negative metastatic breast cancer (HR+ HER2- MBC), the correlation between the level of expression of HR and the clinical efficacy of CDK4/6 inhibitors remains undefined. Methods: We identified consecutive patients with HR+ HER2- MBC starting a CDK4/6 inhibitor (palbociclib, ribociclib or abemaciclib) plus either an aromatase inhibitor or fulvestrant between Jan 2018 - Oct 2023 from an institutional cancer registry. Expression level of HR was stratified as high (H) (Allred score 7-8), moderate (M) (Allred score 5-6) or low (L) (Allred score 3-4) for both estrogen (ER) and progesterone receptors (PR). Patients were evaluated from start of treatment to December 2023, last visit or death, whichever came earlier. Median progression-free survival (mPFS) and overall survival (mOS) were endpoints. We evaluated the association of HR expression levels with mPFS and mOS using log-rank test and multivariate Cox regression modelling. Results: We examined data from 436 women with HR+ HER2- MBC. Median age at treatment was 60.5 yr. Majority of patients received the treatment in the first-line setting (72.5%), with palbociclib (54.1%), ribociclib (31.9%) and abemaciclib (14.0%) as the CDK4/6 inhibitor. In the population that received first-line treatment, ER expression levels were H (83.5%), M (11.4%) and L (5.1%) respectively. ER expression levels were strongly associated with mPFS and mOS. For ER H, M and L expressions, mPFS were 29.4m, 9.2m and 2.9m ( p<0.001); mOS were 52.1m, 40.6m and 11.6m ( p<0.001), respectively. In multivariate analysis, ER expression levels remain strongly predictive for both mPFS and mOS after adjustment for clinicopathological risk factors (ER L vs H, mPFS HR 10.6, p<0.001; mOS HR 4.66, p<0.001; ER M vs H, mPFS HR 4.90, p<0.001; mOS HR 2.06, p=0.05). Findings were similar for the second line and beyond population. In the ER-high expression cohort, the PR expression levels also correlate strongly with treatment efficacy and survival, with mPFS of 40.8m, 24.5m, 24.0m, 14.1m ( p<0.001) and mOS of NR, 53.3m, 48.1m, 26.9m ( p<0.001) respectively for PR H, M, L and zero expressions. Conclusions: In this real-world cohort of patients with HR+ HER2- MBC, we observed that the semi-quantitative HR expression level subgrouping is a strong predictor for the efficacy of treatment with CDK4/6 inhibitors. In contrast to patients with high HR expression levels, the small population with ER-low expression derived very limited benefits from the standard endocrine therapy with CDK4/6 inhibitors. Our findings provided a practical tool to guide the selection of the appropriate systemic therapy for individual patients.
How overall survival is conditioned in the progression to treatment with cyclin inhibitors plus endocrine treatment in metastatic breast cancer with luminal phenotype.
Authors: Prieto Garcia ANA , Morales Murillo Serafin , Tuset Der-abrain Noemí , Rodriguez Gonzalez Gara , Gasol Cudos Ariadna 
Published: June 2024

e13079 Background: CDK4/6 inhibitors plus endocrinotherapy (ET) is the standard first-line treatment for metastatic breast cancer with a luminal phenotype. However, the response to this treatment is highly dependent on its previous efficacy. Methods: We analyzed the overall survival in a cohort of 127 patients with metastatic luminal breast cancer in progression after treatment with CDK4/6 inhibitors plus ET. Results: The median age of the group was 67 years (41-96), the interval time between initial diagnosis and first recurrence was 0 in 41 (32%), 1-60 months in 37 (29%) and more than 60 months in 39 (38%). The first line in the metastatic setting was CDK4/6 plus ET in 81 patients (64%), ET in 15 (12%) and 31 (24%) were treated with chemotherapy. The status of HER2 expression was HER2 low in 77% and 43 % had visceral metastases disease. The median progression-free survival for the patients treated with CDK4/6 inhibitors plus ET was 9 months, with a total of deaths of 69 (55%). Overall survival after progression on CDK4/6 plus ET was 38 months (28 – 47) and the most important factor for overall survival was the response time to treatment with CDK4/6 inhibitors plus ET. Conclusions: The most important factor for overall survival is the duration of treatment with CDK4/6 inhibitors plus ET. Patients with a response time of less than 6 months had a median overall survival after progression of 11 months (3 – 19), while the 6- to 12-month group had a median of 39 months (19 – 59) and the group with more than 12 months had the best prognosis with a median overall survival of 53 months (37 – 68). We need to improve the new treatment options for patients who respond for less than 6 months to treatment with CDK4/6 plus ET.
Toxicity differences in CDK 4/6 inhibitors seen in Asian and Pacific Islanders.
Authors: Gushiken Brooke , Braun-Inglis Christa M. , Workman Tyler , Fukui Jami Aya 
Published: June 2024

e13086 Background: Cyclin-dependent kinases (CDK) 4/6 inhibitors are the standard of care, first line treatment for hormone receptor positive metastatic breast cancer and adjuvant high-risk hormone receptor positive early stage breast cancer along with endocrine therapy. There have been multiple clinical trials validating the effectiveness, along with toxicities of these agents; however, the majority of these trials lack ethnic diversity. This shortcoming limits the ability to apply these findings in diverse patient populations, especially among Asian and Pacific Islanders in Hawaii. Objective: To determine if the toxicity profile of CDK 4/6 inhibitors in women with breast cancer is different among patients at a community oncology practice in Hawaii, in which the majority of patients are Asian, Pacific Islander or a combination of both when compared to three landmark trials. Methods: A retrospective analysis of thirty-two patients with hormone receptor positive, HER2 negative metastatic or high risk breast cancer who started endocrine therapy and CDK 4/6 inhibitor therapy (abemaciclib, ribociclib, or palbociclib) between 2018-2023. Graded toxicities of each individual patient based on CTCAE criteria V. 5, along with demographic data was reviewed and compared to three main registration trials for these agents (MONARCH-3, MONALEESA-2, PALOMA-2). Results: Combined results from the three large randomized trials reported an average of 75% of participants were Caucasian, as compared to 15% in the Hawaii data. While 19% percent of participants from the combined large randomized trials reported being of Asian descent, none of these trials reported a breakdown of Asians versus Pacific Islanders. In the Hawaii sample, 41% were reported as Pacific Islander and 41% reported as Asian, 15% Caucasian, with the final 3% reported as Hispanic. Collective analysis of the FDA registration trials contained 0% Pacific Islander, 19.8% Asian, 74.3% White, 1.5% Black, and 4.4% Other. The majority of all toxicities of all grades were higher in the Hawaii population as compared to the three national trials, except for neutropenia with ribociclib and diarrhea with palbociclib (Table). Conclusions: The Hawaii analysis that was primarily comprised of Asians and Pacific Islanders revealed an increased incidence of toxicities, despite starting at lower doses rates for all CDK 4/6 inhibitors. This data analysis begins to highlight the importance of representative populations in clinical trials for the most effective and safest care of diverse populations. [Table: see text]
Body composition measures as a determinant of alpelisib-related toxicity.
Authors: Shachar Eliya , Raphael Ari , Katz Uriel , Kessner Rivka , Strulov Shachar Shlomit 
Published: June 2024

e13093 Background: Body composition has emerged as an important prognostic factor in patients treated with cancer. Severe depletion of skeletal muscle, sarcopenia, has been associated with poor performance status and worse oncological outcomes. We studied patients with metastatic breast cancer receiving alpelisib, to determine if sarcopenia and additional body composition measures accounting for muscle and adiposity are associated with toxicity. Methods: A retrospective observational analysis was conducted, including 38 women with metastatic breast cancer and a PIK3CA mutation, treated with alpelisib as advanced line of therapy. Sarcopenia was determined by measuring skeletal muscle cross-sectional area at the third lumbar vertebra using computerized tomography. Various body composition metrics were assessed along with drug toxicity, dose reductions, treatment discontinuation, and hospitalizations. Results: Sarcopenia was observed in half of the patients (n=19, 50%), spanning normal weight, overweight, and obese individuals. Among the body composition measures, lower skeletal muscle density (SMD) was associated with an increased risk of treatment-related hyperglycaemia (P=0.03). Additionally, lower visceral adipose tissue (VAT) was associated with alpelisib-induced rash (P=0.04) and hospitalizations (P=0.04). Notably, alpelisib treatment discontinuation was not impacted by alpelisib toxicity. Conclusions: Body composition measures, specifically SMD and VAT may provide an opportunity to identify patients at higher risk for severe alpelisib related hyperglycemia, and cutaneous toxicity. These findings suggest the potential use of body composition assessment to predict toxicity, allowing for personalized therapeutic observation and intervention.