Featured Publications
Perspectives of Patients About Artificial Intelligence in Health Care
Khullar D, Casalino LP, Qian Y, Lu Y, Krumholz HM, Aneja S. Perspectives of Patients About Artificial Intelligence in Health Care. JAMA Network Open 2022, 5: e2210309. PMID: 35507346, PMCID: PMC9069257, DOI: 10.1001/jamanetworkopen.2022.10309.Peer-Reviewed Original ResearchPrevalence of Missing Data in the National Cancer Database and Association With Overall Survival
Yang DX, Khera R, Miccio JA, Jairam V, Chang E, Yu JB, Park HS, Krumholz HM, Aneja S. Prevalence of Missing Data in the National Cancer Database and Association With Overall Survival. JAMA Network Open 2021, 4: e211793. PMID: 33755165, PMCID: PMC7988369, DOI: 10.1001/jamanetworkopen.2021.1793.Peer-Reviewed Original ResearchConceptsNational Cancer DatabaseNon-small cell lung cancerOverall survivalCell lung cancerCancer DatabaseMedical recordsLung cancerProstate cancerBreast cancerPatient recordsComplete dataRetrospective cohort studyCohort studyCancer RegistryCommon cancerVariables of interestHigh prevalenceMAIN OUTCOMEPatientsClinical advancementReal-world data sourcesCancerPrevalenceSurvivalHeterogeneous differencesComparison of radiomic feature aggregation methods for patients with multiple tumors
Chang E, Joel MZ, Chang HY, Du J, Khanna O, Omuro A, Chiang V, Aneja S. Comparison of radiomic feature aggregation methods for patients with multiple tumors. Scientific Reports 2021, 11: 9758. PMID: 33963236, PMCID: PMC8105371, DOI: 10.1038/s41598-021-89114-6.Peer-Reviewed Original ResearchConceptsCox proportional hazards modelCox proportional hazardsProportional hazards modelBrain metastasesRadiomic featuresHazards modelProportional hazardsStandard Cox proportional hazards modelMultifocal brain metastasesMultiple brain metastasesNumber of patientsPatient-level outcomesHigher concordance indexRadiomic feature analysisRandom survival forest modelSurvival modelsDifferent tumor volumesMultifocal tumorsCancer outcomesMultiple tumorsMetastatic cancerConcordance indexTumor volumePatientsTumor types
2022
NIMG-02. PACS-INTEGRATED AUTO-SEGMENTATION WORKFLOW FOR BRAIN METASTASES USING NNU-NET
Jekel L, Bousabarah K, Lin M, Merkaj S, Kaur M, Avesta A, Aneja S, Omuro A, Chiang V, Scheffler B, Aboian M. NIMG-02. PACS-INTEGRATED AUTO-SEGMENTATION WORKFLOW FOR BRAIN METASTASES USING NNU-NET. Neuro-Oncology 2022, 24: vii162-vii162. PMCID: PMC9661012, DOI: 10.1093/neuonc/noac209.622.Peer-Reviewed Original ResearchDeep learning algorithm to predict pathologic complete response to neoadjuvant chemotherapy for breast cancer prior to treatment.
Choi R, Joel M, Hui M, Aneja S. Deep learning algorithm to predict pathologic complete response to neoadjuvant chemotherapy for breast cancer prior to treatment. Journal Of Clinical Oncology 2022, 40: 600-600. DOI: 10.1200/jco.2022.40.16_suppl.600.Peer-Reviewed Original ResearchPathologic complete responseNeoadjuvant chemotherapyBreast cancerComplete responseBreast MRIImproved disease-free survivalDisease-free survivalStage breast cancerPre-treatment predictionSubsets of ageNAC initiationOverall survivalPCR rateTreatment initiationUnnecessary toxicityTumor sizeSingle institutionDisease groupPatient levelPrognostic dataChemotherapyPatientsDiscordant predictionsCancerTotal test set
2019
Multi-Institutional Validation of Deep Learning for Pretreatment Identification of Extranodal Extension in Head and Neck Squamous Cell Carcinoma.
Kann BH, Hicks DF, Payabvash S, Mahajan A, Du J, Gupta V, Park HS, Yu JB, Yarbrough WG, Burtness BA, Husain ZA, Aneja S. Multi-Institutional Validation of Deep Learning for Pretreatment Identification of Extranodal Extension in Head and Neck Squamous Cell Carcinoma. Journal Of Clinical Oncology 2019, 38: 1304-1311. PMID: 31815574, DOI: 10.1200/jco.19.02031.Peer-Reviewed Original ResearchConceptsNeck squamous cell carcinomaExtranodal extensionSquamous cell carcinomaLymph nodesCell carcinomaContrast-enhanced CT scanDiagnostic abilityBoard-certified neuroradiologistsTreatment escalationCancer Genome AtlasPathologic confirmationPretreatment identificationDiagnostic challengeExternal validation data setsPathology resultsPretreatment imagingPoor prognosticatorClinical utilityCT scanPatientsClinical decisionHNSCCDiagnostic accuracyInstitutional ValidationGenome AtlasComparative Effectiveness of SBRT
Aneja S, Kumar R, Yu J. Comparative Effectiveness of SBRT. 2019, 415-424. DOI: 10.1007/978-3-030-16924-4_34.Peer-Reviewed Original ResearchStereotactic body radiation therapyAlternative treatment modalityBody radiation therapyComparative effectiveness studiesCost-effectiveness studiesLarge database analysisRetrospective seriesTreatment modalitiesRadiation therapySBRT treatmentComparative effectivenessEffectiveness studiesDatabase analysisStereotactic treatmentTreatmentPatientsLungTherapyProstateLiverBrain
2016
The Effect of Marital Status on Health-Related Quality of Life in Elderly Patients Undergoing Radiation Therapy
Aneja S, Yu J. The Effect of Marital Status on Health-Related Quality of Life in Elderly Patients Undergoing Radiation Therapy. International Journal Of Radiation Oncology • Biology • Physics 2016, 96: s161. DOI: 10.1016/j.ijrobp.2016.06.389.Peer-Reviewed Original Research