Bibliographic record
Abstract
We thank Noe, Oldenbuettel and Jaeger for their interest in our article focusing on tenofovir alafenamide (TAF). They express concern that our article is “lacking a critical discussion about the increasing evidence of TAF promoting relevant weight gain.” We think that this is an unfair criticism because we submitted our manuscript before the initial uncontrolled report by Gomez et al. 1 was published and the ADVANCE study was presented and subsequently published 2. There were no reports of weight gain associated with TAF therapy at the time at which we submitted our article. As reported in our article, every randomized clinical trial comparing TAF to tenofovir disoproxil fumarate (TDF) has shown improved renal and bone safety of TAF compared with TDF. Since publication of our paper, this was further supported by the DISCOVER study of HIV pre-exposure prophylaxis which enrolled 5387 patients, 2694 of whom received emtricitabine (FTC) combined with TAF (FTC/TAF) and 2693 of whom received FTC/TDF. At week 48, there was a 1.0-kg increase in weight in FTC/TAF recipients compared with no change in weight in FTC/TDF recipients 3. While this difference was statistically significant in a study of nearly 5400 participants, its clinical significance is questionable. The weight gain in FTC/TAF recipients in the DISCOVER study is similar to the 1.1–1.3 kg weight gain at week 48 in the Gilead 4030 study 4, in which patients also received an integrase inhibitor (either dolutegravir or bictegravir), a drug class independently associated with weight gain, so the contribution of TAF to the small amount of weight gain in this study cannot be determined. The annual weight gain reported in patients receiving TAF in the DISCOVER study and the Gilead 4030 study is similar to normal annual weight gain in the general adult population 5. The ADVANCE study demonstrated greater weight gain at 48 weeks with TAF than with TDF in African patients who also received emtricitabine and dolutegravir, with a greater effect on weight in women than in men. It also demonstrated greater weight gain with dolutegravir than with efavirenz, when both were combined with TDF/FTC. The magnitude of weight gain 48 weeks after initiating antiretroviral therapy in this study in patients receiving dolutegravir in both the TDF- and TAF-containing arms has never been reported previously and may be unique to African patients, especially African women. A recent analysis of randomized clinical trials confirms that women and black patients gain more weight on antiretroviral therapy than men and non-black patients 6. This study demonstrated that low baseline CD4 count was the strongest predictor of weight gain 6, and it should be noted the CD4 counts at initiation of antiretroviral therapy are lower in Africa than in high-income countries. The modest increase in weight on TAF compared with TDF requires further study over extended periods of time in different populations, and such studies need to also measure weight gain-associated morbidities, such as type 2 diabetes mellitus and fatty liver disease. The practice of medicine frequently involves competing risks. Perhaps the indisputable improved renal and bone safety of TAF relative to TDF is associated with a slight increase in weight. If so, clinicians will need to consider the relative merits of the benefits and risks of TAF just as they do with all drug therapy.
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 | 0.008 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.040 | 0.044 |
| Insufficient payload (model declined to judge) | 0.012 | 0.011 |
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".