Erin Craig

All Publications

• A review of survival stacking: a method to cast survival regression analysis as a classification problem. The international journal of biostatistics Craig, E., Zhong, C., Tibshirani, R. 2025

  Abstract

  While there are many well-developed data science methods for classification and regression, there are relatively few methods for working with right-censored data. Here, we review survival stacking, a method for casting a survival regression analysis problem as a classification problem, thereby allowing the use of general classification methods and software in a survival setting. Inspired by the Cox partial likelihood, survival stacking collects features and outcomes of survival data in a large data frame with a binary outcome. We show that survival stacking with logistic regression is approximately equivalent to the Cox proportional hazards model. We further illustrate survival stacking on real and simulated data. By reframing survival regression problems as classification problems, survival stacking removes the reliance on specialized tools for survival regression, and makes it straightforward for data scientists to use well-known learning algorithms and software for classification in the survival setting. This in turn lowers the barrier for flexible survival modeling.

  View details for DOI 10.1515/ijb-2022-0055

  View details for PubMedID 40147074

• Disease diagnostics using machine learning of B cell and T cell receptor sequences. Science (New York, N.Y.) Zaslavsky, M. E., Craig, E., Michuda, J. K., Sehgal, N., Ram-Mohan, N., Lee, J. Y., Nguyen, K. D., Hoh, R. A., Pham, T. D., Röltgen, K., Lam, B., Parsons, E. S., Macwana, S. R., DeJager, W., Drapeau, E. M., Roskin, K. M., Cunningham-Rundles, C., Moody, M. A., Haynes, B. F., Goldman, J. D., Heath, J. R., Chinthrajah, R. S., Nadeau, K. C., Pinsky, B. A., Blish, C. A., Hensley, S. E., Jensen, K., Meyer, E., Balboni, I., Utz, P. J., Merrill, J. T., Guthridge, J. M., James, J. A., Yang, S., Tibshirani, R., Kundaje, A., Boyd, S. D. 2025; 387 (6736): eadp2407

  Abstract

  Clinical diagnosis typically incorporates physical examination, patient history, various laboratory tests, and imaging studies but makes limited use of the human immune system's own record of antigen exposures encoded by receptors on B cells and T cells. We analyzed immune receptor datasets from 593 individuals to develop MAchine Learning for Immunological Diagnosis, an interpretive framework to screen for multiple illnesses simultaneously or precisely test for one condition. This approach detects specific infections, autoimmune disorders, vaccine responses, and disease severity differences. Human-interpretable features of the model recapitulate known immune responses to severe acute respiratory syndrome coronavirus 2, influenza, and human immunodeficiency virus, highlight antigen-specific receptors, and reveal distinct characteristics of systemic lupus erythematosus and type-1 diabetes autoreactivity. This analysis framework has broad potential for scientific and clinical interpretation of immune responses.

  View details for DOI 10.1126/science.adp2407

  View details for PubMedID 39977494

• CAR19 monitoring by peripheral blood immunophenotyping reveals histology-specific expansion and toxicity. Blood advances Hamilton, M. P., Craig, E., Gentille Sanchez, C., Mina, A., Tamaresis, J., Kirmani, N., Ehlinger, Z., Syal, S., Good, Z., Sworder, B., Schroers-Martin, J., Lu, Y., Muffly, L., Negrin, R. S., Arai, S., Lowsky, R., Meyer, E., Rezvani, A. R., Shizuru, J. A., Weng, W. K., Shiraz, P., Sidana, S., Bharadwaj, S., Smith, M., Dahiya, S., Sahaf, B., Kurtz, D. M., Mackall, C. L., Tibshirani, R., Alizadeh, A. A., Frank, M. J., Miklos, D. B. 2024

  Abstract

  Chimeric antigen receptor (CAR) T cells directed against CD19 (CAR19) are a revolutionary treatment for B-cell lymphomas. CAR19 cell expansion is necessary for CAR19 function but is also associated with toxicity. To define the impact of CAR19 expansion on patient outcomes, we prospectively followed a cohort of 236 patients treated with CAR19 (brexucabtagene autoleucel or axicabtagene ciloleucel) for mantle cell (MCL), follicular (FL), and large B-cell lymphoma (LBCL) over the course of five years and obtained CAR19 expansion data using peripheral blood immunophenotyping for 188 of these patients. CAR19 expansion was higher in patients with MCL compared to other lymphoma histologic subtypes. Notably, patients with MCL had increased toxicity and required four-fold higher cumulative steroid doses than patients with LBCL. CAR19 expansion was associated with the development of cytokine release syndrome (CRS), immune effector cell associated neurotoxicity syndrome (ICANS), and the requirement for granulocyte colony stimulating factor (GCSF) after day 14 post-infusion. Younger patients and those with elevated lactate dehydrogenase (LDH) had significantly higher CAR19 expansion. In general, no association between CAR19 expansion and LBCL treatment response was observed. However, when controlling for tumor burden, we found that lower CAR19 expansion in conjunction with low LDH was associated with improved outcomes in LBCL. In sum, this study finds CAR19 expansion principally associates with CAR-related toxicity. Additionally, CAR19 expansion as measured by peripheral blood immunophenotyping may be dispensable to favorable outcomes in LBCL.

  View details for DOI 10.1182/bloodadvances.2024012637

  View details for PubMedID 38498731