Shi-Yi Wang, MD, PhD
Senior Research Scientist in EpidemiologyCards
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Titles
Senior Research Scientist in Epidemiology
Biography
Dr. Wang is an Associate Professor at the Yale School of Public Health, faculty member of Cancer Outcomes, Public Policy and Effectiveness Research (COPPER) Center, and faculty member of Public Health Modeling Concentration, Yale School of Public Health. His primary interests focus on outcomes research and decision science. He is interested in combining systematic literature reviews, secondary data analyses, and simulation modeling to examine issues that are critical to clinicians and policy makers’ decision making. He has been working on several breast cancer projects, including an evaluation of preoperative breast MRI, development of an individualized decision aid to help radiotherapy decision-making, and assessment of sentinel lymph node biopsy for patients with ductal carcinoma in situ. He is also evaluating end-of-life care quality. He has served as the primary investigator or co-investigator in several projects (funded by Yale Cancer Center, AHRQ, NCI, ACS, and PCORI).
Appointments
Chronic Disease Epidemiology
Senior Research ScientistPrimaryChronic Disease Epidemiology
LecturerSecondary
Other Departments & Organizations
Education & Training
- PhD
- University of Minnesota (2012)
- MD
- Taipei Medical College (1992)
Research
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Overview
Medical Research Interests
Public Health Interests
ORCID
0000-0002-3294-5784
Research at a Glance
Yale Co-Authors
Publications Timeline
Research Interests
Cary P Gross, MD
Xiaomei Ma, PhD
Rong Wang, PhD
Michaela Dinan, PhD
Michael S. Leapman, MD, MHS
Natalia Kunst, PhD
Breast Neoplasms
Terminal Care
Publications
2026
Potential benefits and harms of screening strategies for monoclonal gammopathy of undetermined significance in the US: A simulation study
Ahmad I, Wang R, Neparidze N, Lange J, Wang S. Potential benefits and harms of screening strategies for monoclonal gammopathy of undetermined significance in the US: A simulation study. Clinical Lymphoma Myeloma & Leukemia 2026 DOI: 10.1016/j.clml.2026.06.001.Peer-Reviewed Original ResearchConceptsMultiple myelomaMonoclonal gammopathyMM patientsScreening strategiesMGUS casesPotential harms of overdiagnosisRisk factorsEnd Results databasePotential harmHarms of overdiagnosisEarly detectionRisk of overdiagnosisBody mass indexHigh-risk individualsScreening benefitsMicro AbstractLack of evidenceScreening frequencyResults databasePremalignant conditionMGUSMM incidenceMass indexGeneral populationGammopathyImmunomodulatory Agent Adherence Trajectories and Survival Among Older Patients With Multiple Myeloma.
Wang R, Ji M, Neparidze N, Ma X, Chang S, Wang S. Immunomodulatory Agent Adherence Trajectories and Survival Among Older Patients With Multiple Myeloma. JCO Oncology Practice 2026, op2500615. PMID: 42081788, DOI: 10.1200/op-25-00615.Peer-Reviewed Original ResearchAltmetricConceptsPoor adherence groupMultiple myelomaAdherence groupIMiD treatmentCox proportional hazards regression modelsCharacteristics associated with adherenceProportional hazards regression modelsSEER-Medicare databaseNon-Hispanic black patientsNon-Hispanic white patientsHazards regression modelsAssociated with adherenceSurvival outcomesRenal failureImmunomodulatory agentsLogistic regression modelsSEER-MedicareOlder patientsWhite patientsBlack patientsBone diseaseGroup 3Comorbidity burdenPatientsComorbid conditionsTreatment Patterns Across Lines of Therapy for Advanced Non‐Small Cell Lung Cancer in the United States
Lee D, Li Y, Yang S, Chiang A, Soulos P, Gross C, Wang S. Treatment Patterns Across Lines of Therapy for Advanced Non‐Small Cell Lung Cancer in the United States. Cancer Medicine 2026, 15: e71736. PMID: 42007970, PMCID: PMC13094514, DOI: 10.1002/cam4.71736.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsProgrammed cell death ligand 1Advanced non-small cell lung cancerNon-small cell lung cancerFirst-line therapyEpidermal growth factor receptorCell lung cancerDiscontinuation ratesRetrospective cohort studyALK rearrangementEGFR-mutantTreatment patternsFlatiron Health electronic health record-derived databaseLung cancerElectronic health record-derived databaseCell death ligand 1Death-ligand 1Lines of therapyTargetable driver alterationsGrowth factor receptorDeidentified patient dataANSCLC patientsTherapy linesTolerated treatmentBiomarker groupsDriver alterationsQIM26-284: Practice-Level Variation in ECOG Performance Status Documentation in Advanced Non–Small Cell Lung Cancer
Li Y, Wang S, Zhang Y, Yang S, Lee D, Soulos P, Wang X, Gross C, Chiang A. QIM26-284: Practice-Level Variation in ECOG Performance Status Documentation in Advanced Non–Small Cell Lung Cancer. Journal Of The National Comprehensive Cancer Network 2026, 24 DOI: 10.6004/jnccn.2025.7441.Peer-Reviewed Original ResearchQuantifying the contribution of modifiable risk factors for progression of MGUS to multiple myeloma in a Veteran population
Wang M, Sigel B, Liu L, Huber J, Ji M, Schoen M, Sanfilippo K, Thomas T, Colditz G, Hsu S, Wang S, Chang S. Quantifying the contribution of modifiable risk factors for progression of MGUS to multiple myeloma in a Veteran population. International Journal Of Cancer 2026, 159: 618-628. PMID: 41813601, PMCID: PMC13004480, DOI: 10.1002/ijc.70412.Peer-Reviewed Original ResearchAltmetricConceptsMultiple myelomaRisk factorsContribution of modifiable risk factorsVeteran populationVeterans Health AdministrationPopulation attributable fractionModifiable risk factorsExcess body mass indexProgression of MGUS to multiple myelomaMGUS to multiple myelomaBody mass indexPlasma cell dyscrasiaRisk of deathAttributable fractionAgent Orange exposureProgressive burdenRetrospective cohort studyHealth AdministrationWeight managementPotential intervention strategiesUnited States veteran populationLifestyle modificationPrevention strategiesCohort studyGeneral populationThe association between body fatness and prevalent MGUS in the U.S. general population
Ji M, Huber J, Wang M, Lan T, Colditz G, Wang S, Chang S. The association between body fatness and prevalent MGUS in the U.S. general population. Cancer Epidemiology 2026, 101: 103021. PMID: 41702266, PMCID: PMC13081065, DOI: 10.1016/j.canep.2026.103021.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsDual-energy X-ray absorptiometryObesity markersBioelectrical impedance analysisNHANES IIIConfidence intervalsBody fat percentageU.S. general populationFat-free massMultivariate logistic regression analysisLogistic regression analysisContinuous NHANESDual-energy X-ray absorptiometry measurementsNational HealthBaseline BMINHANESOdds ratioFat percentageX-ray absorptiometryU.S. populationGeneral populationBody fatLogistic regressionBody compositionOddsTetrapolar bioelectrical impedance analysisA Taxonomy for Assessing Real-World Targeted Cancer Therapy Options in the Context of Broad Genomic Profiling
Wang X, Long J, Rothen J, Huang S, Soulos P, Goldberg S, Robinson T, Ma S, Mamtani R, Presley C, Wang S, Kunst N, Gross C, Dinan M. A Taxonomy for Assessing Real-World Targeted Cancer Therapy Options in the Context of Broad Genomic Profiling. Journal Of The National Comprehensive Cancer Network 2026, 24: e257131. PMID: 41698347, PMCID: PMC13112471, DOI: 10.6004/jnccn.2025.7131.Peer-Reviewed Original ResearchThis study introduces Y-MATRIX, a taxonomy classifying genomic profiling results by clinical actionability, showing increased actionable findings in advanced lung cancer from 2017 to 2023.Overestimation of multiple myeloma survival from cancer registry data
Huber J, Wang M, Wang R, Schoen M, Colditz G, Wang S, Chang S. Overestimation of multiple myeloma survival from cancer registry data. Journal Of The National Cancer Institute 2026, djag028. PMID: 41652897, PMCID: PMC12967285, DOI: 10.1093/jnci/djag028.Peer-Reviewed Original ResearchAltmetricConceptsSymptomatic MMMultiple myelomaFive-year relative survival estimatesSurvival statisticsCancer registry dataRelative survival estimatesMM managementPremalignant conditionSurveillance, EpidemiologyMultiple myeloma survivalRegistry dataMedian survivalMM survivalMyeloma survivalSEERPopulation levelSurvival estimatesSurvivalMyelomaMonthsStatisticallyInclusionEpidemiologyPatientsAdoption and Regional Variation of Prostate-Specific Membrane Antigen Positron Emission Tomography in the United States.
Leapman M, Long J, Westvold S, Rabil M, Sprenkle P, Kim I, Spilberg G, Saperstein L, Fallah J, Suzman D, Lerro C, Xu J, Rivera D, Kluetz P, Karnes R, Dinan M, Mitchell A, Kunst N, Wang S, Ma X, Gross C. Adoption and Regional Variation of Prostate-Specific Membrane Antigen Positron Emission Tomography in the United States. JCO Oncology Practice 2026, op2500617. PMID: 41632928, DOI: 10.1200/op-25-00617.Peer-Reviewed Original ResearchThis study investigates the rapid adoption of PSMA-PET imaging for prostate cancer in the U.S., highlighting increased usage since 2021 and disparities based on income and education.Smoldering multiple myeloma in the United States: a population-based analysis
Wang S, Wang R, Schoen M, Huber J, Feuer E, Ruhl J, Neparidze N, Ma X, Davidoff A, Chang S. Smoldering multiple myeloma in the United States: a population-based analysis. Blood Advances 2026, 10: 661-664. PMID: 41213002, PMCID: PMC12870838, DOI: 10.1182/bloodadvances.2025017817.Peer-Reviewed Original ResearchAltmetric
Academic Achievements & Community Involvement
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Honors
honor The Population Science Research Prize
01/31/2017Other AwardYale Cancer CenterDetailsUnited Stateshonor The Distinguished Student Mentor Award
06/30/2016Other AwardYale School of Public HealthDetailsUnited States
News
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News
- May 06, 2025
Genetic Test Underused in Cancer Care
- August 07, 2023
Screening Mammograms Carry Risks for Older Women, Study Finds
- May 05, 2023
Becca Levy and the Fight Against Ageism
- March 05, 2023
Improving Care of Patients Receiving Advanced Cancer Treatment
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New Haven, CT 06510