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    Developing and Validating an Automatic Support System for Tumor Coding in Pathology Reports in Spanish
    (American Society of Clinical Oncology (ASCO), 2025-02)
    Fabián Villena
    ;
    Pablo Báez
    ;
    Sergio Peñafiel
    ;
    Matías Rojas
    ;
    Inti Paredes
    Purpose Pathology reports provide valuable information for cancer registries to understand, plan, and implement strategies to mitigate the impact of cancer. However, coding essential information from unstructured reports is performed by experts in a time-consuming manual process. We developed and validated a novel two-step automatic coding system that first recognizes tumor morphology and topography mentions from free text and then suggests codes from the International Classification of Diseases for Oncology (ICD-O) in Spanish. Materials and Methods We created an annotated corpus of tumor morphology and topography mentions consisting of 1,101 documents. We combined it with the CANTEMIST corpus (Cancer Text Mining Shared Task). Specifically, we implemented a named entity recognition (NER) model using the bidirectional long short-term memory network-conditional random field architecture enhanced with a stacked embedding layer. We applied transfer learning from state-of-the-art pretrained language models to obtain high-quality contextual representations, thus improving the detection of entities. The mentions found using this model were subsequently oded using a search engine tailored to the ICD-O codes. Results Our NER models achieved an F1 score of 0.86 and 0.90 for tumor morphology and topography, respectively. The overall performance of our automatic coding system achieved an accuracy at five suggestions of 0.72 and 0.65 for tumor morphology and topography, respectively. Conclusion These results demonstrate the feasibility of implementing natural language processing tools in the routine of a cancer center to extract and code valuable information from pathology reports. Our recommender system allows reliable and transparent coding at the moment of consultation. This publication shares the annotated corpus in Spanish, annotation guidelines, and source code to reproduce our experiments.
    Scopus© Citations 3  1
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    Scopus© Citations 26  16
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    Cardiovascular Assessment Tool for Breast Cancer Survivors and Oncology Providers: Usability Study
    (2021)
    Kathryn E Weaver
    ;
    Heidi D Klepin
    ;
    Brian J Wells
    ;
    Emily V Dressler
    ;
    Karen M Winkfield
    <jats:sec> <jats:title>Background</jats:title> <jats:p>Cardiovascular health is of increasing concern to breast cancer survivors and their health care providers, as many survivors are more likely to die from cardiovascular disease than cancer. Implementing clinical decision support tools to address cardiovascular risk factor awareness in the oncology setting may enhance survivors’ attainment or maintenance of cardiovascular health.</jats:p> </jats:sec> <jats:sec> <jats:title>Objective</jats:title> <jats:p>We sought to evaluate survivors’ awareness of cardiovascular risk factors and examine the usability of a novel electronic health record enabled cardiovascular health tool from the perspective of both breast cancer survivors and oncology providers.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>Breast cancer survivors (n=49) recruited from a survivorship clinic interacted with the cardiovascular health tool and completed pre and posttool assessments about cardiovascular health knowledge and perceptions of the tool. Oncologists, physician assistants, and nurse practitioners (n=20) who provide care to survivors also viewed the cardiovascular health tool and completed assessments of perceived usability and acceptability.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>Enrolled breast cancer survivors (84% White race, 4% Hispanic ethnicity) had been diagnosed 10.8 years ago (SD 6.0) with American Joint Committee on Cancer stage 0, I, or II (45/49, 92%). Prior to viewing the tool, 65% of survivors (32/49) reported not knowing their level for one or more cardiovascular health factors (range 0-4). On average, only 45% (range 0%-86%) of survivors’ known cardiovascular health factors were at an ideal level. More than 50% of survivors had ideal smoking status (45/48, 94%) or blood glucose level (29/45, 64%); meanwhile, less than 50% had ideal blood pressure (12/49, 24%), body mass index (12/49, 24%), cholesterol level (17/35, 49%), diet (7/49, 14%), and physical activity (10/49. 20%). More than 90% of survivors thought the tool was easy to understand (46/47, 98%), improved their understanding (43/47, 91%), and was helpful (45/47, 96%); overall, 94% (44/47 survivors) liked the tool. A majority of survivors (44/47, 94%) thought oncologists should discuss cardiovascular health during survivorship care. Most (12/20, 60%) oncology providers (female: 12/20, 60%; physicians: 14/20, 70%) had been practicing for more than 5 years. Most providers agreed the tool provided useful information (18/20, 90%), would help their effectiveness (18/20, 90%), was easy to use (20/20, 100%), and presented information in a useful format (19/20, 95%); and 85% of providers (17/20) reported they would use the tool most or all of the time when providing survivorship care.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>These usability data demonstrate acceptability of a cardiovascular health clinical decision support tool in oncology practices. Oncology providers and breast cancer survivors would likely value the integration of such apps in survivorship care. By increasing awareness and communication regarding cardiovascular health, electronic health record–enabled tools may improve survivorship care delivery for breast cancer and ultimately patient outcomes.</jats:p> </jats:sec>
      10Scopus© Citations 10
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    Textual inference for eligibility criteria resolution in clinical trials
    (2015)
    Chaitanya Shivade
    ;
    Courtney Hebert
    ;
    Marcelo Lopetegui
    ;
    Marie-Catherine de Marneffe
    ;
    Eric Fosler-Lussier
      8Scopus© Citations 31