Isotretinoin and Thyroid Dysfunction: A Call for Routine Monitoring
Bibliographic record
Abstract
Isotretinoin is a widely prescribed medication for severe acne and other dermatological conditions. While effective in managing acne, some of its systemic effects were widely discussed. However, its impact particularly on thyroid function remains underexplored. This narrative review highlights current evidence on the relationship between isotretinoin use and thyroid dysfunction, evaluating the need for routine thyroid function testing to help clinicians assess the risk of thyroid dysfunction in their patients. We searched PubMed, Scopus, and Google Scholar from inception to February 2025. Interpretation was guided by a systematic approach emphasizing study relevance, methodological quality, and recency. Inclusion criteria focused on peer‐reviewed research addressing isotretinoin’s impact on thyroid function. Study designs, sample sizes, and risk of bias were critically assessed to maintain objectivity and reliability in synthesizing current evidence. Studies consistently report alterations in thyroid hormone levels during isotretinoin therapy, including elevated thyroid‐stimulating hormone (TSH) and decreased free triiodothyronine (FT3) and free thyroxine (FT4) levels. Studies suggest that these changes may be mediated through mechanisms involving thyroid cell apoptosis, immunomodulatory effects, or central regulatory disruptions. Females and individuals undergoing prolonged isotretinoin therapy appear to be at higher risk. These findings highlight the importance of routine thyroid function monitoring in patients on isotretinoin, particularly those with a predisposition to autoimmune disorders or prolonged treatment courses. Further research with larger sample sizes and rigorous methodologies is needed to comprehend the underlying mechanisms and refine clinical guidelines. This review emphasizes on the need for a multidisciplinary approach involving dermatologists and endocrinologists to ensure optimal patient care and safety.
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 | 0.063 | 0.157 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.006 | 0.014 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.007 | 0.006 |
| 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".