Efficacy and adverse events of oral isotretinoin for acne: a systematic review
Bibliographic record
Abstract
Acne vulgaris, usually just referred to as acne, is the most common skin disease. It causes red spots, pus‐filled spots and blackheads and can vary in severity from mild to severe. Because it can be very visible, it can cause anxiety, reduced self‐esteem and stigma. In cases of more severe acne that hasn't improved with other treatments, a powerful drug taken orally (by mouth) called isotretinoin can be prescribed by doctors. This study, from Canada, reviewed evidence from randomized controlled trials (RCTs) to assess the efficacy and safety of isotretinoin. RCTs are studies in which a number of patients are randomly allocated to two or more test groups, one of which will be a ‘control’ group (who typically receive either no treatment, standard care or a placebo), while the other groups will receive the specific treatments being tested. The different groups of patients are then monitored in the exact same way, allowing for direct comparison between different treatments. Eleven trials were identified, involving a total of 760 patients ‐ mostly males. Across all trials, isotretinoin reduced acne lesion counts (number of spots), and always by a greater amount than controls, which were either placebo, oral antibiotics, or another control type. The frequency of adverse events, meaning unwanted side effects, was twice as high with isotretinoin (751 events) compared to control (388 events). More than half of all adverse events related to skin dryness. Adverse events caused 12 of the 760 participants to withdrawal from trials, due to the development of Stevens‐Johnson Syndrome, cheilitis, xerosis, acne flare, photophobia, elevated liver enzymes, decreased appetite, headaches and depressed mood. This review suggests that isotretinoin is effective in reducing acne lesion counts, but adverse events are common.
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.
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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".