Current Trends and Outcomes in Cellular Therapy Activity in the United States, Including Prospective Patient-Reported Outcomes Data Collection in the Center for International Blood and Marrow Transplant Research Registry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Center for International Blood and Marrow Transplant Research (CIBMTR) prepares an annual set of summary slides to summarize the trends in transplantation and cellular therapies. For the first time in the 2023 summary slides, the CIBMTR incorporated data for patients receiving chimeric antigen receptor T cell (CAR-T) infusions. In addition, data on patient-reported outcomes (PROs) are included. This report aims to update the annual trends in US hematopoietic cell transplantation (HCT) activity and incorporate data on the use of CAR-T therapies. A second aim is to present and describe the development, implementation, and current status of PRO data collection. In August 2020, the CIBMTR launched the Protocol for Collection of Patient-Reported Outcomes Data (CIBMTR PRO Protocol). The CIBMTR PRO Protocol operates under a centralized infrastructure to reduce the burden to centers. Specifically, PRO data are collected from a prospective convenience sample of adult HCT and CAR-T recipients who received treatment at contributing centers and consented for research. Data are merged and stored with the clinical data and used under the governance of the CIBMTR Research Database Protocol. Participants answer a series of surveys developed by the Patient Reported Outcomes Measurement Information System (PROMIS) focusing on physical, social and emotional, and other measures assessing financial well-being, occupational functioning, and social determinants of health. To complement traditionally measured clinical outcomes, the surveys are administered at the same time points at which clinical data are routinely collected. As of September 2023, PRO data have been collected from 993 patients across 25 different centers. With the goal of incorporating these important patient perspectives into standard clinical care, the CIBMTR has added the PRO data to Data Back to Centers (DBtC). Through expanding the data types represented in the registry, the CIBMTR aims to support holistic research accounting for the patients' perspective in improving patient outcomes. CIBMTR PRO data aim to provide a foundation for future large-scale, population-level evaluations to identify areas for improvement, emerging disparities in access and health outcomes (eg, by age, race, and ethnicity), and new therapies that may impact current treatment guidelines. Continuing to collect and grow the PRO data is critical for understanding these changes and identifying methods for improving patients' quality of life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it