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Record W2792117618 · doi:10.1097/qad.0000000000001769

Concerns about a study on sexually transmitted infections after initiation of HIV preexposure prophylaxis

2018· letter· en· W2792117618 on OpenAlexaboutno aff
Julia L. Marcus, Jonathan E. Volk, Jonathan M. Snowden

Bibliographic record

VenueAIDS · 2018
Typeletter
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersNational Institute on Minority Health and Health DisparitiesNational Institute of Allergy and Infectious DiseasesKaiser Permanente
KeywordsPre-exposure prophylaxisGonorrheaMedicineChlamydiaRisk compensationHuman immunodeficiency virus (HIV)Incidence (geometry)Men who have sex with menDemographyGonococcal infectionGynecologySyphilisFamily medicineSexually transmitted diseaseImmunology

Abstract

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An article in AIDS by Nguyen et al. [1] tests the hypothesis that use of HIV preexposure prophylaxis (PrEP) leads to risk compensation, and thus to increased rates of sexually transmitted infections (STIs). Nguyen et al.[1] use a Canadian clinic-based sample of MSM to make two comparisons: STI rates in PrEP users in the 12 months after PrEP initiation compared with 12 months before PrEP initiation, and STI rates in PrEP users in the 12 months after PrEP initiation compared with postexposure prophylaxis (PEP) users in the 12 months after PEP use. They conclude that their data support the risk compensation hypothesis. However, we have four concerns about this study, particularly with respect to study design and the degree to which the results support the conclusions of Nguyen et al.[1]. First, as Nguyen et al.[1] point out, gonorrhea and chlamydia incidence nearly doubled among men in Quebec during 2010–2015, so we would expect to see increases in STI rates over time regardless of PrEP initiation. Thus, any significant finding in the preinitiation/postinitiation comparison may be driven by these temporal changes rather than PrEP use. Analytic approaches exist to address secular changes over time; one is to compare PrEP users to a control group also experiencing the temporal change but not the exposure condition (i.e. PrEP), as in difference-in-differences analysis [2]. Second, PEP users are not a valid control group for PrEP users. Although PEP users have had at least one potential HIV exposure, those who have ongoing HIV risk would ideally transition from PEP to PrEP, while those with only a brief period of risk or a single exposure would not be indicated for PrEP [3]. Nguyen et al.[1] did not present data on transitions from PEP to PrEP or discuss how these were handled in the analyses. If PEP patients with ongoing risk transitioned to PrEP, the higher rates of STIs observed would likely reflect the appropriate prescribing of PrEP rather than risk compensation. Furthermore, most PEP users report a decrease in condomless sex in the 12 months post-PEP [4]; indeed, a comparison to STI rates in the 12 months prior to PEP use may have been more appropriate. Third, Nguyen et al.[1] do not acknowledge or discuss their null findings, and some conclusions are based on interpreting nonsignificant results as meaningful differences. For the post-PrEP vs. pre-PrEP comparison, there was no observed increase in rates of anal, oral, urethral, or any gonorrhea; syphilis; or anal, oral, or urethral chlamydia, and the conclusion that overall STI rates were higher post-PrEP vs. pre-PrEP was based on a result that was not statistically significant after adjustment for frequency of STI screening [adjusted incidence rate ratio (aIRR) 1.39, 95% CI 0.98–1.96]. For the post-PrEP vs. post-PEP comparison, there was no observed increase in rates of anal, oral, urethral, or any gonorrhea; syphilis; or oral chlamydia. Finally, we do not understand the conclusion that the highest rate ratios were for anal and oral gonorrhea, nor the argument of Nguyen et al.[1] that increases in asymptomatic STIs indicate risk compensation. The rate ratios for anal and oral gonorrhea in the post-PrEP/pre-PrEP comparison were above and below the null value of 1, respectively, and neither approached statistical significance (anal: aIRR 1.29, 95% CI 0.57–2.89; oral: aIRR 0.85, 95% CI 0.38–1.90). Even if Nguyen et al.[1] had in fact observed increases in asymptomatic STIs, it is not clear why this would be consistent with risk compensation. The higher frequency of screening among PrEP users will detect asymptomatic STIs that would otherwise have gone undiagnosed, a bias that is unlikely to be fully removed by adjusting for number of STI tests. Thus, an increase in symptomatic STIs would be a better marker of risk compensation because it would be independent of differences in screening. Most urethral gonorrhea infections in men are symptomatic [5], yet Nguyen et al.[1] observed no increased risk of urethral gonorrhea post-PrEP vs. pre-PrEP (aIRR 0.60, 95% CI 0.22–1.64) or post-PrEP vs. post-PEP (aIRR 2.42, 95% CI 0.47–12.55). There is a pressing need for further research on clinical and behavioral PrEP outcomes, given the rapidly shifting dialogue about PrEP uptake, the optimal delivery of this health service, and its potential effects on individuals’ sexual behaviors and the sexual health of populations. That said, our concerns about the study by Nguyen et al.[1], as well as similar concerns expressed about other recent studies on PrEP-associated risk compensation [6,7], highlight that there is an equally pressing need for rigorous research design and measured study interpretation that does not overreach the observed findings. Acknowledgements This work was supported by a Kaiser Permanente Northern California Community Benefit research grant, and by the National Institute of Allergy and Infectious Diseases (K01 122853). Conflicts of interest J.L.M. reports past research grant support from Merck. J.E.V. and J.M.S. report no potential conflicts. Sources of funding: This work was supported by a Kaiser Permanente Northern California Community Benefit research grant, and by the National Institute of Allergy and Infectious Diseases (K01 122853).

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.029
GPT teacher head0.335
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

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Citations5
Published2018
Admission routes1
Has abstractyes

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