Abstract 2316: Benefits Of Clinical Trial Participation For Risk Factor Control: Experience From The SPS3 Study
Bibliographic record
Abstract
Objective: To assess for unplanned effects of trial participation as measured by changes in smoking, alcohol use, and exercise. Background: Trial effect is a non-specific element of trial participation that has been difficult to quantify. Recent trials are beginning to measure this with promising results. The SPS3 study tests the effects of antiplatelet therapy and intensive blood pressure control on stroke recurrence and cognitive decline. The protocol does not mandate interventions for modifying lifestyle behaviors but local study investigators provide guidance for these changes at their discretion. This provides an opportunity to evaluate a “trial effect”, beyond the study interventions. Design/Methods: SPS3 subjects who completed at least one 3-month visit were included (n=2935). Definitions used by CDC for risk factors were applied to SPS3. Hypothesis tests were performed to determine differences between SPS3 group at baseline and general population (CDC, n=210000). Kaplan-Meier plots were used to determine time from baseline to behavior changes. Log-rank tests were performed to determine influence of age, gender, education, and ethnicity in risk factor outcomes. Results: At baseline, smoking status was comparable between SPS3 and CDC groups (19.9%, 20.6% respectively); alcohol use was significantly lower (27.9%, 52% respectively); and exercise was comparable (50.8%, 48.8% respectively). Of the 583 smokers at baseline; 323 (55%) stopped while 152 (47%) restarted over the mean follow-up of 36 months. Of the 820 regular alcohol users at baseline, 536 (65%) stopped while 278 (52%) restarted again. Of the 1444 who did not exercise at least 3 times per week at baseline, 1209 (84%) started while 855 (71%) stopped again. There were no significant differences in these three health behaviors by age, gender, education, or race. A marginally significant effect by age was observed related to alcohol. Subjects ≤64 yr old at baseline were more likely to stop regular alcohol use than those >64 (p=0.054). Conclusion: Independent of the study intervention, SPS3 participants significantly modified their health behaviors. Our findings suggest that it is important to address trial effect and its impact on the outcomes.
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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 | 0.125 | 0.127 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".