Publication summaries

1. Clonal Hematopoiesis of Indeterminate Potential After Radiation Therapy. International Journal of Radiation Oncology*Biology*Physics, 2025.

   This study examined whether radiation therapy contributes to clonal hematopoiesis of indeterminate potential (CHIP), a blood condition linked to higher risk of blood cancers and cardiovascular disease. Analyzing blood samples from 489 cancer patients treated with radiation and comparing them with 854 patients who had neither radiation nor chemotherapy, the authors detected CHIP in 23% of irradiated patients and found a higher likelihood of CHIP after radiation, with risk rising as the radiation dose increased. The findings suggest that radiation dose and technique may influence CHIP development, which matters for understanding the long-term risks of cancer treatment.

2. Introducing mCODEGPT as a zero-shot information extraction from clinical free text data tool for cancer research. Communications Medicine, 2025.

   Clinical notes about cancer patients hold valuable information, but extracting it in a structured form is difficult, and traditional natural language processing methods require extensive expert annotation and model training for each type of data. This paper introduces mCODEGPT, a tool for zero-shot information extraction from clinical free text, meaning it can pull structured data from notes without task-specific training. The aim is a more efficient and accurate way to standardize and structure clinical text for cancer research.

3. Artificial intelligence across the cancer care continuum. Cancer, 2025.

   This review surveys how artificial intelligence is being applied across the full span of cancer care, from risk assessment and early detection through treatment, survivorship, and end-of-life care. It describes AI tools that combine data sources such as multi-omics and electronic health records to personalize prevention, improve medical imaging and pathology interpretation, and refine treatment and radiation planning, while noting that clinical adoption depends on rigorous validation, data privacy, and reducing bias. The authors emphasize that AI works best alongside clinical expertise and that responsible development and clinician education are essential.

4. Advancing the science of genomic learning healthcare systems. Learning Health Systems, 2025.

   Genomic learning healthcare systems (gLHS) integrate genomics into routine clinical care, but they remain concentrated in major academic centers and largely operate independently. Drawing on deliberations of an expert group convened by the National Human Genome Research Institute plus relevant literature, this paper identifies characteristics of exemplary gLHS and argues that sharing their methods and tools would broaden access to these innovations. It reports that several such systems have agreed to form a coalition to gather, evaluate, and disseminate best practices, which the authors say could improve genomic variant curation and interpretation, diagnostic accuracy, and patient care.

5. Vanderbilt Clinical Informatics Center Education Strategy: To Infinity and Beyond!. Applied Clinical Informatics, 2025.

   This paper describes how the Vanderbilt Clinical Informatics Center (VCLIC), based in the Department of Biomedical Informatics, educates and trains faculty, staff, students, and trainees in clinical informatics across the university and health system. Its approach combines formal programs, such as a clinical informatics graduate course, a master's in applied clinical informatics, a medical student course, a graduate medical education elective, and a clinical informatics fellowship, with informal offerings like workshops, seminars, conference-style events, short instructive videos, and hackathons. The described programs have trained hundreds of participants, and VCLIC-held events drew high satisfaction ratings, with an average score of 4.63 out of 5 and every event averaging above 4.

6. Radiomics and Deep Learning Prediction of Immunotherapy-Induced Pneumonitis From Computed Tomography. JCO Clinical Cancer Informatics, 2025.

   Immune checkpoint inhibitors can trigger pneumonitis, a potentially life-threatening lung inflammation that may force patients to stop treatment, so predicting who is at risk could make therapy safer. Using pre-treatment chest CT scans from cancer patients at Vanderbilt University Medical Center, the researchers built three image-based models and found that a deep learning model reading the raw scans (AUC 0.819) outperformed a traditional radiomics-only approach (AUC 0.747), while combining the two added little. The work suggests that analyzing pre-treatment scans with deep learning could help flag at-risk patients, supporting safer immunotherapy use and better stratification in drug trials.

7. Minimal Common Oncology Data Elements Genomics Pilot Project: Enhancing Oncology Research Through Electronic Health Record Interoperability at Vanderbilt University Medical Center. JCO Clinical Cancer Informatics, 2024.

   Researchers at Vanderbilt University Medical Center made their Epic electronic health record compatible with mCODE, a FHIR-based consensus data standard for sharing cancer patient data. They built an end-to-end pipeline that converted EHR data into mCODE-compliant profiles and created a web application that visualizes genomic data and provides cancer risk assessments. The project is a proof of concept that mCODE can be integrated into a major health system's existing infrastructure, while also documenting the current limits of FHIR APIs for supporting complex data analysis in oncology research.

8. Integrating electronic health records (EHRs) to facilitate cancer biomarker testing: Real-world implementation barriers and solutions.. Journal of Clinical Oncology, 2024.

   This work reports on a 2023 summit convened by the Association of Cancer Care Centers, where 37 oncologists, pathologists, nurse navigators, and administrators from varied settings discussed how to integrate cancer biomarker test ordering and results into the electronic health record. Participants identified benefits such as greater efficiency, streamlined communication, and improved clinical decision-making, along with success factors like strong clinical champions, administrative buy-in, and dedicated IT support. Reported barriers included variable EHR interoperability, use of multiple external reference labs, inconsistent nomenclature, and limited internal IT resources, pointing to what is needed to make EHR-integrated biomarker workflows more common.

9. Incorporating Integrated Diagnostics into Precision Oncology Care: Proceedings of a Workshop., 2024.

   This is a published proceedings volume from a workshop on incorporating integrated diagnostics into precision oncology care. The available abstract does not describe the workshop's specific content or conclusions, noting only that the material can be read online, downloaded as a PDF, or ordered in print.

10. Prediction of Effectiveness and Toxicities of Immune Checkpoint Inhibitors Using Real-World Patient Data. JCO Clinical Cancer Informatics, 2024.

    This study used routine electronic health record data from more than 2,200 cancer patients treated with immune checkpoint inhibitors to build machine learning models that predict serious immune-related side effects (hepatitis, colitis, and pneumonitis) as well as one-year overall survival. The random forest models each drew on outcome-specific sets of features, such as laboratory measurements aggregated over time, and reached AUCs of roughly 0.73 to 0.76. The authors describe it as, to their knowledge, the first machine learning approach to assess an individual patient's checkpoint-inhibitor risk-benefit profile predominantly from routine structured EHR data, which could help inform treatment decisions and clinical trial selection.

11. Clinician Perspectives Regarding the Impact of Information Technology on Multidisciplinary Tumor Boards: A National Comprehensive Cancer Network Survey. JCO Clinical Cancer Informatics, 2023.

    A National Comprehensive Cancer Network workgroup surveyed oncology clinicians across member institutions in early 2022 to understand how information technology tools, such as electronic health records and virtual conferencing, affect multidisciplinary tumor boards. Nearly all respondents reported that their tumor boards now include participants attending virtually, and most said attendance increased after virtualization while discussion quality stayed the same or improved. The survey also revealed gaps between how important clinicians consider EHR features (like adding patients for presentation or documenting recommendations in the EHR) and how often they can actually do those things, highlighting where EHR integration falls short of the ideal.

12. Next-generation phenotyping: introducing phecodeX for enhanced discovery research in medical phenomics. Bioinformatics, 2023.

    Phecodes are widely used phenotype definitions built from International Classification of Diseases codes, but the existing version (v1.2) was designed mainly for common, complex diseases in adults and has structural limitations. This paper introduces phecodeX, an expanded version with a revised structure and 1,761 new codes that add detail in areas previously under-represented, including infectious disease, pregnancy, congenital anomalies, and neonatology. The result is a more robust representation of the medical phenome for discovery research, and it is made freely available on GitHub.

13. Accuracy and Reliability of Chatbot Responses to Physician Questions. JAMA Network Open, 2023.

    This study tested how well a chatbot (ChatGPT) answered real medical questions posed by clinicians. Thirty-three physicians across 17 specialties wrote 284 questions of varying difficulty, then graded the chatbot's answers for accuracy on a 6-point scale and completeness on a 3-point scale, also comparing GPT-3.5 with GPT-4 and consistency over time. The answers were largely accurate, with a median accuracy score of 5.5 (between almost completely and completely correct), suggesting such tools could make medical information more accessible while still carrying limitations that matter in clinical settings.

14. Identification and Characterization of Avoidable Hospital Admissions in Patients With Lung Cancer. Journal of the National Comprehensive Cancer Network, 2023.

    A multidisciplinary team retrospectively reviewed the records of lung cancer patients hospitalized during treatment in 2018 to distinguish avoidable from unavoidable admissions. Across 319 admissions in 188 patients, 15% were judged avoidable, and errors in medication management caused about a quarter of those; cancer-related symptoms accounted for most hospitalizations overall. Patients with avoidable admissions had markedly shorter median survival (1.6 vs 9.7 months), pointing to opportunities to reduce hospital burden through better symptom control, medication reconciliation, and timely hospice referral.

15. Implementing Innovation: Informatics-Based Technologies to Improve Care Delivery and Clinical Research. American Society of Clinical Oncology Educational Book, 2023.

    This review examines three informatics initiatives intended to improve cancer care delivery and clinical research: the Clinical Trials Rapid Activation Consortium (CTRAC), the Minimal Common Oncology Data Elements (mCODE) data standard, and electronic patient-reported outcomes. Each initiative is at a different stage of maturity, and together they illustrate how new technology can speed clinical trial activation, improve data sharing between cancer centers, and enhance patient care. The authors frame these examples as part of a broader movement toward patient-centered data and interoperability in oncology.

16. Accelerated curation of checkpoint inhibitor-induced colitis cases from electronic health records. JAMIA Open, 2023.

    The authors built an automated pipeline using a natural-language-processing model (BERT) to find electronic health record notes documenting colitis caused by immune checkpoint inhibitor cancer therapy, a step needed to assemble training data for predictive models. The multi-stage pipeline segmented long notes, filtered out likely false positives, and highlighted the colitis-relevant text, identifying ICI-colitis notes with 84% precision while cutting the manual chart-review workload by 75%. Because manual curation from EHR notes is burdensome, the approach could accelerate research and be adapted to other clinical topics.

17. On the cusp: Considering the impact of artificial intelligence language models in healthcare. Med (New York, N.Y.), 2023.

    This short commentary reflects on how AI language models such as ChatGPT could transform healthcare by spreading medical knowledge and personalizing patient education. The authors caution that, before these tools can be safely integrated into care, further research and robust oversight mechanisms are needed to ensure their accuracy and reliability.

18. Assessing the Accuracy and Reliability of AI-Generated Medical Responses: An Evaluation of the Chat-GPT Model (under review)., 2023.

    This preprint evaluated how accurately and completely ChatGPT answered 284 medical questions written and graded by 33 physicians across 17 specialties. Answers were largely accurate (median accuracy 5.5 on a 6-point scale) and complete (median completeness 3, the top of the 3-point scale, meaning complete plus additional context), and answers that initially scored poorly often improved when the same questions were re-asked 8 to 17 days later. The authors conclude that ChatGPT generated largely accurate medical information as judged by specialist physicians, but with important limitations that require further research and validation.

19. A Unified Approach to Clinical Informatics Education for Undergraduate and Graduate Medical Education. AMIA ... Annual Symposium proceedings. AMIA Symposium, 2022.

    This paper describes a single clinical informatics course that Vanderbilt University Medical Center built to teach both undergraduate and graduate medical learners, structured around four activities: didactic sessions, an "informatics history and physical" in which learners observe clinical workflows and propose an informatics solution, hands-on time alongside practicing clinical informaticians, and case-based group work, with objectives modeled on the clinical informatics fellowship curriculum. Twenty-three learners completed the course, and feedback suggested it met its planned goals. The authors present it as a feasible model other institutions could adopt to address gaps in clinical informatics training.

20. Associations of influenza vaccination with severity of immune-related adverse events in patients with advanced thoracic cancers on immune checkpoint inhibitors. ERJ open research, 2022.

    This retrospective cohort study examined whether receiving an influenza vaccine around the time of immune checkpoint inhibitor therapy was associated with the severity of immune-related adverse events in patients with advanced thoracic cancer. Vaccinated patients had less severe immune-related adverse events overall and a lower risk of severe (grade 3-5) events, while vaccination showed no association with survival times. The authors conclude that influenza vaccination did not increase treatment toxicity in these patients and was linked to a reduced risk of severe immune-related events.

21. Two Uncomplicated Pregnancies on Alectinib in a Woman With Metastatic ALK-Rearranged NSCLC: A Case Report. JTO Clinical and Research Reports, 2022.

    This case report describes a woman with metastatic ALK-rearranged non-small cell lung cancer who was treated with the ALK inhibitor alectinib throughout two pregnancies, both of which had uncomplicated obstetrical and postnatal courses. Because safety data for alectinib during pregnancy are limited, the authors note this as only the second such reported case, and in it the drug did not appear to affect fetal or early childhood development. They caution that this does not exclude undetectable or delayed toxic effects and that additional study is needed.

22. The Future of Telemedicine in Oncology. Journal of the National Comprehensive Cancer Network, 2022.

    This article discusses how the COVID-19 pandemic drove a large surge in telemedicine use in oncology, with usage later settling below its early-pandemic peak but above pre-pandemic levels. The authors note that most oncology providers view telemedicine as beneficial and likely to stay, but point to barriers that hinder equitable delivery, including older age, rural residence, lower socioeconomic status, and racial/ethnic disparities. They argue that addressing these disparities, expanding broadband access, and educating both patients and providers are essential to telemedicine's future in cancer care.

23. Innovation in Electronic Health Records for Oncology Care, Research, and Surveillance: Proceedings of a Workshop., 2022.

    This document is the proceedings of a 2022 public workshop, hosted by the National Academies' National Cancer Policy Forum and Computer Science and Telecommunications Board, examining how electronic health records are used across cancer care, research, and disease surveillance. It summarizes presentations and discussions on opportunities to improve patient care and outcomes through collaboration that enhances the development, implementation, and use of EHRs in oncology. It captures the workshop's conversations rather than reporting original study results.

24. Adoption of Patient-Generated Health Data in Oncology: A Report From the NCCN EHR Oncology Advisory Group. Journal of the National Comprehensive Cancer Network, 2022.

    This report from an NCCN advisory workgroup surveyed member cancer institutions to assess how widely patient-generated health data, such as patient-reported outcomes, is collected and integrated into electronic health records. Among the 23 responding institutions, use of such data was nearly universal and most embedded at least some of it into their EHRs, though many still relied on tools that were not fully integrated and governance practices varied. The authors conclude that patient-generated health data has not yet reached its full potential in oncology and recommend steps including governance processes that include patients.

25. Oncologist Perspectives on Telemedicine for Patients With Cancer: A National Comprehensive Cancer Network Survey. JCO Oncology Practice, 2021.

    A National Comprehensive Cancer Network workgroup surveyed 1,038 oncology providers at 26 institutions in summer 2020 about using telemedicine after the COVID-19 pandemic pushed care online. Most providers found phone and video visits worked as well as or better than in-person visits for reviewing routine follow-up data, though far fewer felt telemedicine was as good for building a personal connection with patients, and nearly all said adverse outcomes rarely or never occurred. Providers estimated that about 46% of visits could be handled virtually going forward, while flagging barriers such as patients' access to technology, clinical workflows, and uncertainty about insurance coverage.

26. Follow-up Interactive Long-Term Expert Ranking (FILTER): a crowdsourcing platform to adjudicate risk for survivorship care. JAMIA open, 2021.

    The authors built an online platform called FILTER that lets oncologists and other survivorship experts judge which cancer survivors are at higher risk of complications during long-term follow-up. Participants compare pairs of synthetic patient cases, and an Elo ranking algorithm converts these head-to-head judgments into relative risk scores. The tool is live as a cloud-based web application and is intended to help tailor survivorship care to individual risk, which the authors suggest could improve both resource allocation and patient outcomes.

27. My Cancer Genome: Coevolution of Precision Oncology and a Molecular Oncology Knowledgebase. JCO Clinical Cancer Informatics, 2021.

    My Cancer Genome, a knowledge resource launched in 2011 to help clinicians interpret genomic test results for cancer treatment, originally relied on labor-intensive manual writing of each web page, which limited how quickly it could grow. The team redesigned it around an assertion-based data model, in which cause-and-effect statements are curated and stored so that reusable templates automatically generate and update the site's pages. This approach let the resource scale to more than 9,100 clinical trial pages, 18,100 gene and alteration pages, 900 disease pages, and 2,700 drug pages, illustrating how automated page generation can keep a precision oncology resource current as the field advances.

28. Framework for Implementing and Tracking a Molecular Tumor Board at a National Cancer Institute–Designated Comprehensive Cancer Center. The Oncologist, 2021.

    As tumor genetic sequencing panels grew to cover hundreds of genes, oncologists increasingly struggled to interpret the results and choose treatments, so Vanderbilt-Ingram Cancer Center set up two molecular tumor boards: one for its own patients and a global community board open to a wider population. These boards bring together oncologists, pathologists, geneticists, and genetic counselors to review cases and produce formal treatment recommendations documented in the medical record. By December 2020 the boards had discussed over 170 institutional cases from 77 providers plus 58 international cases from six countries, and the authors share their best practices as a framework other institutions can replicate.

29. Women screened for breast cancer are dying from lung cancer: An opportunity to improve lung cancer screening in a mammography population. Journal of Medical Screening, 2021.

    This study examined whether women getting mammograms could also benefit from lung cancer screening, reviewing records of 18,040 women screened for breast cancer in 2015 at two facilities that offered both. Using a natural language processing algorithm plus manual chart review, the team identified 251 women who met USPSTF criteria for lung screening based on age and smoking history, but only 63 (25%) went on to enroll in lung screening. Among those who enrolled, three lung cancers were detected with no deaths, whereas among the 188 who were not screened, seven developed lung cancer and five died, pointing to a missed opportunity to catch lung cancer earlier in women already coming in for breast screening.

30. Learnings From Precision Clinical Trial Matching for Oncology Patients Who Received NGS Testing. JCO Clinical Cancer Informatics, 2021.

    Tumor sequencing reports often suggest clinical trials for patients based on their diagnosis and genetic profile, but those automated lists include many poor matches that physicians must weed out by hand. The authors compared automatically generated trial recommendations against the same lists after manual prescreening and found that trial-specific details, especially whether individual trial arms were still recruiting, were the largest source of false-positive matches. They conclude that building such trial-specific criteria into automated matching, and making trial recruiting status publicly available at the arm level, could substantially reduce false positives and ease the burden on physicians selecting trials for their patients.

31. A retrospective approach to evaluating potential adverse outcomes associated with delay of procedures for cardiovascular and cancer-related diagnoses in the context of COVID-19. Journal of Biomedical Informatics, 2021.

    When Vanderbilt University Medical Center suspended elective procedures and non-urgent visits early in the COVID-19 pandemic, the researchers built an approach using electronic health record data to measure how those delays affected patients. Comparing procedures during the shutdown against the same weeks in 2019, they identified 416 negatively affected surgical procedures and found 27 statistically significant associations between procedure delay and adverse outcomes such as longer hospital stays, in-hospital death, later cancer stage at diagnosis, and lower five-year survival, with clinician review judging 88.9% of those associations plausible and potentially clinically significant. The method gives health systems a way to identify which delayed procedures carry real risk so they can prioritize rescheduling and communicate with patients.

32. Improving Cancer Data Interoperability: The Promise of the Minimal Common Oncology Data Elements (mCODE) Initiative. JCO Clinical Cancer Informatics, 2020.

    This paper describes the Minimal Common Oncology Data Elements (mCODE), a consensus data standard developed through an ASCO-convened work group to make it easier to share structured cancer patient data across electronic health records. The specification is organized into six domains (patient, laboratory/vital, disease, genomics, treatment, and outcome) spanning 23 profiles and 90 data elements, and it advanced through public comment and Health Level 7 balloting to reach its version 1.0 Fast Healthcare Interoperability Resources implementation guide in March 2020. mCODE aims to build shared infrastructure to better connect cancer care and research, is available free, and had pilot implementations underway.

33. Seven decades of chemotherapy clinical trials: a pan-cancer social network analysis. Scientific Reports, 2020.

    The authors performed a social network analysis of authors who published chemotherapy-based prospective cancer trials from 1946 to 2018, tracking how the community grew from fewer than 50 authors to 29,197. By 2018 nearly all authors were connected, but connections tended to cluster within the same or similar fields, a small number of individuals held disproportionate influence, and women were underrepresented and likelier to have lower impact, shorter productive periods, and less centrality. The analysis characterizes the trialist network as a mix of cooperation and competition and projects that parity for new authors by gender may arrive around 2032.

34. Trends in FDA cancer registration trial design over time, 1969-2020.. Journal of Clinical Oncology, 2020.

    This study reviewed the package inserts of 258 FDA-approved oncology drugs to examine how the design of trials supporting cancer drug approvals changed from 1969 to 2020, linking trials to the HemOnc ontology and grouping them into four designs (escalation, in-class comparison, out-of-class switch, and de-escalation). Of 556 registration trials identified, 372 (67%) were randomized controlled trials, and approvals rose exponentially over time. This is a conference abstract.

35. Conceptual Framework to Support Clinical Trial Optimization and End-to-End Enrollment Workflow. JCO Clinical Cancer Informatics, 2019.

    This paper presents a conceptual framework for improving how clinical trials are optimized and how patients are enrolled, and reviews the current state, limitations, and future trends in this space. The framework spans knowledge representation of clinical trials, trial optimization and design, enrollment workflows for prospective patient-trial matching, waitlist management, and strategies for evaluating improvement. It is a framework and review rather than a study reporting new results.

36. Hypertension and use of bevacizumab among patients treated in community settings.. Journal of Clinical Oncology, 2019.

    Using CancerLinQ Discovery, a real-world dataset drawn from US electronic health records, the researchers examined hypertension and blood pressure patterns among breast cancer and lung cancer patients treated with bevacizumab. Among 1,941 breast cancer and 4,590 lung cancer patients treated from 2005 to 2017, more than half had hypertension at baseline, and a large share saw their systolic blood pressure rise by at least 10 mmHg within 120 days of starting bevacizumab, including many who began with normal blood pressure. This is a conference abstract describing real-world blood pressure changes associated with bevacizumab in community-treated patients.

37. Learnings from a pragmatic study to evaluate benefit of performing reflex clinical trial matching and providing clinical decision support to physicians.. Journal of Clinical Oncology, 2019.

    This pragmatic study tested whether automatically triggering a clinical trial match when a patient's tumor sequencing results arrived, then having a research nurse refine the matches and message recommendations to randomized providers, could ease trial enrollment. In a pilot of 60 patients, provider response rate was 94%, but 17% of patients had outdated vital-status records and trial cohort recruiting statuses caused the largest share of false matches (44%). The authors conclude that meaningful gains in trial enrollment require reliable, publicly maintained data on trial recruiting status at the individual arm or cohort level.

38. The Impact of Big Data Research on Practice, Policy, and Cancer Care. American Society of Clinical Oncology Educational Book, 2019.

    This review examines how aggregating and analyzing large data sources can inform cancer clinical practice and policy, focusing on three types: pooled clinical trial data, administrative and insurance claims data, and electronic health record data. It weighs the benefits of each source against their inherent limitations and offers next steps for researchers, clinicians, and policymakers. The authors suggest that combining these data sources, and eventually applying machine learning, could improve knowledge and patient outcomes.

39. Impact of the influenza vaccination on cancer patients undergoing therapy with immune checkpoint inhibitors (ICI).. Journal of Clinical Oncology, 2018.

    This retrospective review of 534 cancer patients treated with immune checkpoint inhibitors at Vanderbilt-Ingram Cancer Center compared those who received the influenza vaccine (72.1%) with those who did not. Vaccinated and unvaccinated patients developed similar overall rates of immune-related adverse events, but among the patients who did develop such events, those who were unvaccinated were more likely to have pneumonitis and to be admitted; separately, unvaccinated patients were more likely to be admitted for flu-related complications. Vaccination did not change progression-free survival but was associated with improved overall survival, suggesting the flu vaccine did not increase toxicity in these patients and may be linked to better outcomes.

40. Phenotype risk scores identify patients with unrecognized Mendelian disease patterns. Science, 2018.

    The authors developed phenotype risk scores (PheRS) that aggregate clinical features from electronic health records according to the patterns of 1,204 known Mendelian diseases, rather than examining symptoms one at a time. The score distinguished cases from controls for five Mendelian diseases, and applying it to 21,701 genotyped individuals uncovered 18 associations between rare genetic variants and Mendelian-consistent phenotypes, including 16 patients whose rare variants were linked to severe outcomes such as organ transplants. The work suggests undiagnosed Mendelian disease may be more common than assumed and that this approach can aid interpretation of rare genetic variants.

41. Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the electronic health record. PloS One, 2017.

    This study compared three ways of grouping electronic health record billing codes (raw ICD-9-CM codes, the Clinical Classification Software groupings, and manually curated phecodes) for how well each captures clinically meaningful phenotypes and reproduces known genetic associations, using 100 phenotypes and 440 SNP-phenotype pairs. Phecodes exactly matched 83 of the 100 phenotypes, compared with 53 for ICD-9-CM and 32 for CCS, and replicated more known genetic associations with generally stronger effect sizes. The results support phecodes as a better-suited coding scheme for phenome-wide association studies in electronic health records.

42. Utility of adding clinical data to a molecular results portal for improving clinical trial prescreening efficiency.. Journal of Clinical Oncology, 2017.

    This study evaluated whether adding minimal clinical data to a genomic results portal could make clinical trial prescreening more efficient for three molecularly driven trials at Vanderbilt-Ingram Cancer Center. Starting from 7,200 patients with sequencing data, gene-level and diagnosis criteria identified 68 potentially eligible patients; adding specific alteration detail removed 29% of them, and adding vital status removed an additional 42% of those remaining. The authors conclude that combining structured clinical and molecular data from the enterprise data warehouse improves prescreening efficiency and reduces manual chart review.

43. Advances in website information resources to aid in clinical practice. American Society of Clinical Oncology educational book / ASCO. American Society of Clinical Oncology. Meeting, 2015.

    This review surveys internet-based information resources that practicing oncologists can use in everyday clinical work, spanning general medicine, oncology-specific tools, and social media. The authors note that the volume of new cancer literature is overwhelming, with a new cancer-related article added to the MEDLINE database roughly every three minutes, and argue that well-chosen online resources can help clinicians organize that flood of information into usable knowledge. It matters because it points busy oncologists toward reliable 'just-in-time' resources to support better patient care.

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