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Glenn Heller, PhD

Attending Biostatistician

Office Phone



New York University

Current Research Interests

Dr. Heller’s current research interests include the design and analysis of phase 2 clinical trials, the analysis of survival data, and the investigation of biomarkers to update patient prognosis. For the analysis of phase 2 studies, he has developed a test statistic that adjusts for patient risk when the patient population is heterogeneous. This approach is applicable in targeted therapy trials, where multiple patient populations are treated under a single protocol. In survival analysis, he has developed a measure of predictive accuracy, based on the concept of explained randomness.  This metric, applied to risk models with survival data, is used to determine the adequacy of a risk classification model for clinical decision making.  Dr. Heller’s work with circulating tumor cells, a biomarker for metastatic disease, has demonstrated both prognostic utility and clinical utility when applied to metastatic prostate cancer patients. Dr. Heller is involved in the design and analysis of laboratory and clinical studies emanating from the Departments of Medicine, Pediatrics, and Surgery.


Selected peer-reviewed publications:

  1. Heller G, Seshan VE, Moskowitz CS, Gonen M. Inference for the difference in the area under the ROC curve derived from nested binary regression models. Biostatistics. 2017. 18: 260-274.

  2. Heller G, Fizazi K, McCormack RT, Molina A, MacLean D, Webb IJ, Saad F, de Bono JS, Scher HI. The added value of circulating tumor cell enumeration to standard markers in assessing prognosis in a metastatic castration-resistant prostate cancer population. Clinical Cancer Research. 2017. 23: 1967-1973.

  3. Heller G, Mo X. Estimating the concordance probability in a survival analysis with a discrete number of risk groups. Lifetime Data Analysis. 2016. 22: 263-279.

  4. Heller G. A measure of explained risk in the proportional hazards model. Biostatistics. 2012. 13: 315-25.

  5. Heller G. Proportional hazards regression with interval censored data using an inverse probability weight. Lifetime Data Analysis. 2011. 17: 373-85.

For a complete list of publications:

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