Assessing Disease Stability of Patients with Myelodysplastic Syndrome for an Age of Blood Randomized Controlled Trial: A Chart Review
Bibliographic record
Abstract
Abstract INTRODUCTION: A randomized crossover design is an efficient way to compare two treatment approaches as patients serve as their own control minimizing between patient variability; however, for the crossover design to be valid the patients disease must be stable during observation period. A crossover design was considered for exploring the age of transfused red cells on quality of life (QoL) in patients with myelodysplastic syndrome (MDS). To determine if this design would be appropriate, a chart review of patients with MDS requiring transfusion was performed. Stable disease was defined by transfusion interval and pre-transfusion hemoglobin. METHODS: Adult patients scheduled for transfusion at two hematology/oncology outpatient clinics (one in an academic hospital center and one at a cancer center) were screened for eligibility. Inclusion criteria included: a diagnosis of MDS; ≥18 years; diagnosed and followed for at least six months. Data were abstracted from electronic health records and charts of eligible patients between the dates of January 1 and June 30, 2013. Information pertaining to hospital admissions, infection, red blood cell (RBC) product utilization, and hematology laboratory test results were captured. Additional information pertaining to the age of RBCs transfused was retrieved from the Transfusion Registry for Utilization, Surveillance, and Tracking database. Data abstraction and entry were 100% verified using source documents. The study was approved by the local research ethics board and informed consent was not required. The primary outcome was proportion of stable patients who received more than 4 transfusions during the 6 months observation period. The criteria for stability were peer reviewed by clinicians who treat MDS patients and included: 1) quartiles 1 and 3 around the median number of days between transfusion episodes was ≤7 days; and, 2) quartiles 1 and 3 around the median pre-RBC transfusion hemoglobin (Hb) count was ≤10g/L. Patient's disease was not considered to be stable if the patient was admitted to hospital for an MDS or co-morbidity related issue within the past 6 months or, if there was severe infections within the past 6 months. Data were analyzed descriptively. Means and standard deviations were reported for continuous variables along with medians and interquartile ranges (IQRs) where appropriate. Proportions were used to describe categorical variables RESULTS: 21/52 (40.4%) of patients screened were eligible for the study (mean age: 79.52 ± 6.03 years; 6 female). Most patients (17/21; 81%) had at least one comorbid illness. Patients experienced a median of 5 transfusion episodes (IQR, 2, 12) over 6 months. The median age of RBCs transfused was 24 days (IQR, 20, 31). 14 patients had at least 4 transfusion episodes during this time and were included in the stability assessment. 2/14 patients had unstable disease: one patient had a median of 11 days between transfusion episodes (IQR, 4.25, 20); another patient had a median pre-transfusion Hb of 91.5 g/L (IQR, 79.75, 97.5) and was considered not stable since quartile 1 exceeded 10g/L. None of the patients had severe infections or were admitted to hospital for MDS or other co-morbid illnesses. Hence 12/14 (85.7%) of patients were considered stable. CONCLUSION: This study introduces a novel approach to assessing clinical stability in transfused patients with MDS. While the criteria for assessing stability were peer reviewed, this approach requires further validation. More than half of patients with MDS in our study (12/21) were considered clinically stable. This approach, once validated, can be used to define stable MDS patients if research using a crossover design is being considered. Disclosures Leber: Novartis Canada: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene Canada: Honoraria, Membership on an entity's Board of Directors or advisory committees.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.045 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".