Isotretinoin therapy and the incidence of acne relapse: a nested case–control study
Bibliographic record
Abstract
BACKGROUND: Previous studies on predictors of acne relapse in patients treated with isotretinoin had either small sample sizes, short follow-up periods, or lacked population-based data. OBJECTIVES: To identify and quantify predictors of acne relapse, and predictors of receiving a second isotretinoin treatment. METHODS: Using the Régie de l'Assurance Maladie du Québec (RAMQ) and Quebec's hospital discharge (Med-Echo) administrative databases, a population-based cohort of 17 351 first-time isotretinoin users was assembled between 1984 and 2003. A nested case-control analysis was performed to determine predictors of acne relapse (as defined by receiving an antiacne medication). A second nested case-control analysis was performed to determine predictors of receiving a second isotretinoin treatment. The index date of cases was the calendar date of dispensing an antiacne medication (isotretinoin or other). Five controls were matched to each case on follow-up time. Rate ratios were estimated using conditional logistic regression. RESULTS: A total of 7100 (41%) subjects experienced an acne relapse. These were matched to 35 500 controls. Being male, under 16 years of age and living in an urban area, and receiving isotretinoin cumulative doses greater than 2450 mg and an isotretinoin treatment longer than 121 days were statistically associated (P < 0.05) with acne relapse. The publishing of the different Canadian acne guidelines had no impact on the incidence of acne relapse (P > 0.05). A total of 4443 (26%) subjects required a second isotretinoin treatment. These were matched to 22 215 controls. There was a greater probability of receiving a second isotretinoin treatment after the publishing of the Canadian acne guidelines (P < 0.05). CONCLUSION: A relatively high rate of subjects experienced an acne relapse after an isotretinoin treatment.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".