A population-level digital histologic biomarker for enhanced prognosis of invasive breast cancer.

Breast cancer is a heterogeneous disease with variable survival outcomes. Pathologists grade the microscopic appearance of breast tissue using the Nottingham criteria, which are qualitative and do not account for noncancerous elements within the tumor microenvironment. Here we present the Histomic Prognostic Signature (HiPS), a comprehensive, interpretable scoring of the survival risk incurred by breast tumor microenvironment morphology. HiPS uses deep learning to accurately map cellular and tissue structures to measure epithelial, stromal, immune, and spatial interaction features. It was developed using a population-level cohort from the Cancer Prevention Study-II and validated using data from three independent cohorts, including the Prostate, Lung, Colorectal, and Ovarian Cancer trial, Cancer Prevention Study-3, and The Cancer Genome Atlas. HiPS consistently outperformed pathologists in predicting survival outcomes, independent of tumor-node-metastasis stage and pertinent variables. This was largely driven by stromal and immune features. In conclusion, HiPS is a robustly validated biomarker to support pathologists and improve patient prognosis.

Does High-Dose Thromboprophylaxis Improve Outcomes in COVID-19 Patients? A Meta-analysis of Comparative Studies.

Background Thromboembolism remains a detrimental complication of novel coronavirus disease (COVID-19) despite the use of prophylactic doses of anticoagulation Objectives This study aimed to compare different thromboprophylaxis strategies in COVID-19 patients Methods We conducted a systematic database search until June 30, 2022. Eligible studies were randomized (RCTs) and nonrandomized studies that compared prophylactic to intermediate or therapeutic doses of anticoagulation in adult patients with COVID-19, admitted to general wards or intensive care unit (ICU). Primary outcomes were mortality, thromboembolism, and bleeding events. Data are analyzed separately in RCTs and non-RCTs and in ICU and non-ICU patients. Results. We identified 682 studies and included 53 eligible studies. Therapeutic anticoagulation showed no mortality benefit over prophylactic anticoagulation in four RCTs (odds ratio [OR] = 0.67, 95% confidence interval [CI], 0.18-2.54). Therapeutic anticoagulation didn't improve mortality in ICU or non-ICU patients. Risk of thromboembolism was significantly lower among non-ICU patients who received enhanced (therapeutic/intermediate) anticoagulation (OR = 0.21, 95% CI, 0.06-0.74). Two additional RCTs (Multiplatform Trial and HEP-COVID), not included in quantitative meta-analysis, analyzed non-ICU patients, and reported a similar benefit with therapeutic-dose anticoagulation. Therapeutic anticoagulation was associated with a significantly higher risk of bleeding events among non-randomized studies (OR = 3.45, 95% CI, 2.32-5.13). Among RCTs, although patients who received therapeutic-dose anticoagulation had higher numbers of bleeding events, these differences were not statistically significant. Studies comparing prophylactic and intermediate-dose anticoagulation showed no differences in primary outcomes. Conclusion There is a lack of mortality benefit with therapeutic-dose over prophylactic-dose anticoagulation in ICU and non-ICU COVID-19 patients. Therapeutic anticoagulation significantly decreased risk of thromboembolism risk in some of the available RCTs, especially among non-ICU patients. This potential benefit, however, may be counter balanced by higher risk of bleeding. Individualized assessment of patient's bleeding risk will ultimately impact the true clinical benefit of anticoagulation in each patient. Finally, we found no mortality or morbidity benefit with intermediate-dose anticoagulation.

NuCLS: A scalable crowdsourcing approach and dataset for nucleus classification and segmentation in breast cancer.

BACKGROUND: Deep learning enables accurate high-resolution mapping of cells and tissue structures that can serve as the foundation of interpretable machine-learning models for computational pathology. However, generating adequate labels for these structures is a critical barrier, given the time and effort required from pathologists. RESULTS: This article describes a novel collaborative framework for engaging crowds of medical students and pathologists to produce quality labels for cell nuclei. We used this approach to produce the NuCLS dataset, containing >220,000 annotations of cell nuclei in breast cancers. This builds on prior work labeling tissue regions to produce an integrated tissue region- and cell-level annotation dataset for training that is the largest such resource for multi-scale analysis of breast cancer histology. This article presents data and analysis results for single and multi-rater annotations from both non-experts and pathologists. We present a novel workflow that uses algorithmic suggestions to collect accurate segmentation data without the need for laborious manual tracing of nuclei. Our results indicate that even noisy algorithmic suggestions do not adversely affect pathologist accuracy and can help non-experts improve annotation quality. We also present a new approach for inferring truth from multiple raters and show that non-experts can produce accurate annotations for visually distinctive classes. CONCLUSIONS: This study is the most extensive systematic exploration of the large-scale use of wisdom-of-the-crowd approaches to generate data for computational pathology applications.

Explainable nucleus classification using Decision Tree Approximation of Learned Embeddings.

MOTIVATION: Nucleus detection, segmentation and classification are fundamental to high-resolution mapping of the tumor microenvironment using whole-slide histopathology images. The growing interest in leveraging the power of deep learning to achieve state-of-the-art performance often comes at the cost of explainability, yet there is general consensus that explainability is critical for trustworthiness and widespread clinical adoption. Unfortunately, current explainability paradigms that rely on pixel saliency heatmaps or superpixel importance scores are not well-suited for nucleus classification. Techniques like Grad-CAM or LIME provide explanations that are indirect, qualitative and/or nonintuitive to pathologists. RESULTS: In this article, we present techniques to enable scalable nuclear detection, segmentation and explainable classification. First, we show how modifications to the widely used Mask R-CNN architecture, including decoupling the detection and classification tasks, improves accuracy and enables learning from hybrid annotation datasets like NuCLS, which contain mixtures of bounding boxes and segmentation boundaries. Second, we introduce an explainability method called Decision Tree Approximation of Learned Embeddings (DTALE), which provides explanations for classification model behavior globally, as well as for individual nuclear predictions. DTALE explanations are simple, quantitative, and can flexibly use any measurable morphological features that make sense to practicing pathologists, without sacrificing model accuracy. Together, these techniques present a step toward realizing the promise of computational pathology in computer-aided diagnosis and discovery of morphologic biomarkers. AVAILABILITY AND IMPLEMENTATION: Relevant code can be found at github.com/CancerDataScience/NuCLS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Clinical Utilization and Cost of Thrombophilia Testing in Patients with Venous Thromboembolism.

Introduction Testing for inherited and acquired thrombophilias adds to the cost of care of patients with venous thromboembolism (VTE), though results may not influence patient management. Methods This is a single-center, retrospective study conducted at Emory University Hospitals from January to December 2015 to (1) determine the pattern of thrombophilia testing in patients with VTE, (2) study the impact of results of thrombophilia testing on clinical decision-making, and (3) determine the direct costs of thrombophilia testing in patients with VTE. Results Of the 266 eligible patients, 189 (71%) underwent testing; 51 (26.9%) tested positive and the results impacted management in 32 (16.9%) of tested patients. Patient undergoing testing were more likely to be younger than 40 years (30.9 vs. 18.2%), have had prior pregnancy loss (9.0 vs. 0%), or known family history of hypercoagulability (24.9 vs. 10.4%), and were less likely to have had provoked VTE (37 vs. 79.2%). The most common thrombophilias tested were antiphospholipid syndrome (60.1%), factor V Leiden (59.7%), and prothrombin gene mutation (57.5%). Direct costs of thrombophilia testing were $2,364.32 per patient, $12,331.55 to diagnose 1 positive, and $19,653.41 per patient-management affected. Conclusion We noted significant variability in selection of patients and panel of tests, sparse utilization of test results in patient management, but high cost associated with thrombophilia testing in patients with VTE. With guidelines advocating selective use of thrombophilia testing and attention to potential impact of test results in patient management, we propose the need for measures at institutional levels to improve test-ordering practices.

Structured crowdsourcing enables convolutional segmentation of histology images.

MOTIVATION: While deep-learning algorithms have demonstrated outstanding performance in semantic image segmentation tasks, large annotation datasets are needed to create accurate models. Annotation of histology images is challenging due to the effort and experience required to carefully delineate tissue structures, and difficulties related to sharing and markup of whole-slide images. RESULTS: We recruited 25 participants, ranging in experience from senior pathologists to medical students, to delineate tissue regions in 151 breast cancer slides using the Digital Slide Archive. Inter-participant discordance was systematically evaluated, revealing low discordance for tumor and stroma, and higher discordance for more subjectively defined or rare tissue classes. Feedback provided by senior participants enabled the generation and curation of 20 000+ annotated tissue regions. Fully convolutional networks trained using these annotations were highly accurate (mean AUC=0.945), and the scale of annotation data provided notable improvements in image classification accuracy. AVAILABILITY AND IMPLEMENTATION: Dataset is freely available at: https://goo.gl/cNM4EL. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Direct oral anticoagulants in patients with venous thromboembolism and thrombophilia: a systematic review and meta-analysis.

Essentials We investigated direct oral anticoagulant (DOAC) use in venous thromboembolism and thrombophilia. A comprehensive search identified 10 studies, 8 of which were included in a meta-analysis. DOACs were overall safe and effective in patients with venous thromboembolism and thrombophilia. Efficacy/safety of DOACs was maintained in low-risk antiphospholipid syndrome patient subgroup. SUMMARY: Background Direct oral anticoagulants (DOACs) are increasingly used in acute and long-term treatment of venous thromboembolism (VTE). However, their role in management of thrombophilia-associated VTE is controversial. Methods Through a comprehensive search on MEDLINE, Cochrane Library, and Clinicaltrials.gov, we identified 10 eligible studies, 8 of which reporting data on 1994 thrombophilia patients were included in a random-effects meta-analysis. Eligible studies were phase 2 to 3 randomized controlled trials comparing DOACs to vitamin K antagonists (VKAs) in patients with VTE, including those with thrombophilia. Results Of eight studies included in meta-analysis, four evaluated rivaroxaban, three dabigatran, and one edoxaban. No results could be obtained on apixaban use. The rates of VTE recurrence (RR, 0.70; 95% CI, 0.34-1.44; I2  = 0%) and major/clinically relevant non-major bleeding events (RR, 0.92; 95% CI, 0.62-1.36; I2  = 23%) were similar between thrombophilia patients treated with DOACs compared to VKAs. Results were comparable to findings in patients without known thrombophilia: RR, 1.02; 95% CI, 0.80-1.30; I2  = 46% for VTE recurrence and RR, 0.72; 95% CI, 0.57-0.90; I2  = 84% for major/clinically relevant non-major bleeding events. Conclusions Rates of VTE recurrence and bleeding events were both low and comparable in patients with various thrombophilias receiving either treatment, suggesting that DOACs are an appropriate treatment option in this population. Due to limited data, it is unclear whether these findings apply to specific subgroups such as high-risk antiphospholipid syndrome, uncommon thrombophilias, or the use of apixaban.

Publisher Correction: Management of Low and Intermediate Risk Adult Rhabdomyosarcoma: A Pooled Survival Analysis of 553 Patients.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Management of Low and Intermediate Risk Adult Rhabdomyosarcoma: A Pooled Survival Analysis of 553 Patients.

This is the second-largest retrospective analysis addressing the controversy of whether adult rhabdomyosarcoma (RMS) should be treated with chemotherapy regimens adopted from pediatric RMS protocols or adult soft-tissue sarcoma protocols. A comprehensive database search identified 553 adults with primary non-metastatic RMS. Increasing age, intermediate-risk disease, no chemotherapy use, anthacycline-based and poor chemotherapy response were significant predictors of poor overall and progression-free survival. In contrast, combined cyclophosphamide-based, cyclophosphamide + anthracycline-based, or cyclophosphamide + ifosfamide + anthracycline-based regimens significantly improved outcomes. Intermediate-risk disease was a significant predictor of poor chemotherapy response. Overall survival of clinical group-III patients was significantly improved if they underwent delayed complete resection. Non-parameningeal clinical group-I patients had the best local control, which was not affected by additional adjuvant radiotherapy. This study highlights the superiority of chemotherapy regimens -adapted from pediatric protocols- compared to anthracycline-based regimens. There is lack of data to support the routine use of adjuvant radiotherapy for non-parameningeal group-I patients. Nonetheless, intensive local therapy should be always considered for those at high risk for local recurrence, including intermediate-risk disease, advanced IRS stage, large tumors or narrow surgical margins. Although practically difficult (due to tumor's rarity), there is a pressing need for high quality randomized controlled trials to provide further guidance.