Kay See Tan, PhD

Assistant Attending Biostatistician

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Kay See Tan, PhD

Office Phone

646-888-8257

Education

University of Pennsylvania

Dr. Tan’s research focuses on the joint modeling of longitudinal and recurrent-event data, particularly when an adverse event triggers outcome assessment in between prescheduled follow-up visits. Her methods estimate covariate-outcome associations when observation times may depend on outcome values and unmeasured patient-level characteristics to ensure patients with more observations are not over-represented in the analysis. She is also interested in methodological issues pertaining to patient-reported measures and cancer surveillance. Dr. Tan serves as the biostatistician for the Department of Anesthesiology and Critical Care as well as the Thoracic Surgery Service. She currently serves as the Membership Director on the Junior Faculty Council at MSK and Assistant Director for the QSURE summer undergraduate internship program.

Publications

Selected peer-reviewed publications:

  1. Impact of increasing age on cause-specific mortality and morbidity in patients with stage I non–small-cell lung cancer: A competing risks analysis. T Eguchi, S Bains, MC Lee, KS Tan, B Hristov, DH Buitrago, MS Bains, … Journal of Clinical Oncology 35 (3), 281-290
  2. Spread through Air Spaces (STAS) Is an Independent Predictor of Recurrence and Lung Cancer–Specific Death in Squamous Cell Carcinoma. S Lu, KS Tan, K Kadota, T Eguchi, S Bains, N Rekhtman, PS Adusumilli, …Journal of Thoracic Oncology 12 (2), 223-234
  3. HPV‐related oropharyngeal cancer: Risk factors for treatment failure in patients managed with primary transoral robotic surgery. JM Kaczmar, KS Tan, DF Heitjan, A Lin, PH Ahn, JG Newman, …Head & neck 38 (1), 59-65
  4. Trends in critical care beds and use among population groups and medicare and medicaid beneficiaries in the United States: 2000–2010. NA Halpern, DA Goldman, KS Tan, SM Pastores. Critical care medicine 44 (8), 1490-1499
  5. Regression modeling of longitudinal data with outcome‐dependent observation times: extensions and comparative evaluation. KS Tan, B French, AB Troxel. Statistics in medicine 33 (27), 4770-4789

Visit PubMed for a full listing of Kay See Tan’s journal articles

Pubmed is an online index of biomedical articles maintained by the U.S. National Library of Medicine and the National Institutes of Health.

Disclosures

Doctors and faculty members often work with pharmaceutical, device, biotechnology, and life sciences companies, and other organizations outside of MSK, to find safe and effective cancer treatments, to improve patient care, and to educate the health care community.

MSK requires doctors and faculty members to report (“disclose”) the relationships and financial interests they have with external entities. As a commitment to transparency with our community, we make that information available to the public.

Kay See Tan discloses the following relationships and financial interests:

No disclosures meeting criteria for time period


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