Philippe Flandre

Background and Objective: Doravirine is among the first‐line recommended treatments for people living with HIV (PLHIV) in the 2025 EACS guidelines. As opposed to tenofovir alafenamide or anti‐integrase, its use was not associated with weight gain in clinical trials, but limited data are currently available in real life. In this cohort study, we investigated weight variation in PLHIV switching to doravirine. Methods: A retrospective cohort analysis was conducted in two Parisian hospitals, including all PLHIV switching to doravirine between January 2019 and September 2022. Body Mass Index (BMI) variation was calculated from 48 months before to 36 months after the switch. Results: Between January 2019 and December 2022, 300 patients were included, with 220 men (73%) and 185 (62%) patients born in France. The main antiretroviral combination before the switch was TAF/FTC/BIC ( n = 47, 16%), and after the switch, doravirine with TDF and 3TC ( n = 202, 67%). Twenty‐eight patients (9.3%) discontinued doravirine after a median duration of 17.5 months. At 12 and 24 months after the switch, the median BMI variation was 0.0 kg/m ² , and this variation remained unchanged regardless of the pre‐switch treatment. These results were less pronounced in subgroups of patients originating from sub‐Saharan Africa (+0.2 and +0.4 kg/m ² ) and in women (+0.3 and 0.5 kg/m ² ). Conclusion: Switching to doravirine led to a weight stabilisation, without reversal of the previously gained weight. In PLHIV at higher risk of weight gain, there was still a slight increase in BMI after the doravirine switch.

Background: The impact of pharmacokinetic variability of cabotegravir (CAB) and rilpivirine (RPV) long-acting (LA) injectable therapy on virological outcomes remains controversial. This study aimed to characterize the variability of CAB and RPV trough concentrations (Ctrough) and to identify the predictors of suboptimal exposure and virologic failure (VF) in a large real-world cohort. Methods: We conducted a multicenter observational study including people with human immunodeficiency virus type 1 (HIV-1) initiating LA-CAB/RPV as maintenance therapy from January to December 2022, in whom CAB and RPV plasma Ctrough were determined as part of therapeutic drug monitoring (TDM). Results: A total of 1674 CAB and 1687 RPV Ctrough measurements were collected from 736 people with HIV-1 (PWH). Significant interindividual variability in concentrations was observed. At month 1/month 3, 20%–30% of PWH had Ctrough <1120 ng/mL for CAB and 32 ng/mL for RPV. Predictors of lower Ctrough were body mass index (BMI) ≥30 kg/m2 and female sex at month 1, and only male sex at steady state. After a median follow-up of 12 (interquartile range, 9–16) months, VF occurred in 2.5% of PWH. At month 6 and month 12, VF was significantly associated with the presence of at least 2 risk factors (obesity, suboptimal Ctrough) (odds ratio [OR], 4.6, P = .047; OR, 5.15, P = .014), and CD4 nadir (OR, 0.56, P = .008; OR, 0.5, P = .001). Conclusions: Our large real-world study confirms significant variability in CAB and RPV exposure, with BMI and sex as key predictors of lower Ctrough. Suboptimal CAB and RPV Ctrough, particularly in people with obesity, increases the risk of VF during the first year of treatment, highlighting the usefulness of TDM in clinical practice.

This work aims to evaluate integrase resistance and its predictors in HIV-1 infected combined antiretroviral therapy (cART) experienced individuals failing a dolutegravir-based regimen. Major resistance mutations (MRM) and genotypic susceptibility score (GSS) of dolutegravir companion drugs were evaluated on plasma genotypic resistance test (GRT) performed at dolutegravir failure. Logistic regression was used to evaluate factors associated to the risk of integrase strand-transfer inhibitors (INSTI)-resistance at dolutegravir failure. We retrospectively analysed 467 individuals. At failure GRT, individuals had been under dolutegravir for a median (IQR) time of 11 (5–20) months; around half of them had never been exposed to INSTI (52%) and 10.7% were at first-line regimen. Fifty-eight (12.4%) individuals showed ≥1 INSTI MRM. Among them, people INSTI-exposed showed significantly higher prevalence of INSTI resistance compared to those who were INSTI naïve [46 (21.2%) versus 9 (3.9%), P < 0.001]. N155H was the most prevalent MRM (5.4%), followed by G140S (4.5%) and Q148H (4.3%). These MRM were more probably present in INSTI-experienced individuals compared to those INSTI naïve. Despite failure, 89.5% of individuals harboured viral strains fully susceptible to dolutegravir and bictegravir and 85.0% to all INSTI. No INSTI exposure before receiving dolutegravir [OR: 0.35 (0.16–0.78), P < 0.010] and a GSS for companion drugs ≥2 (OR: 0.09 [0.04–0.23], P < 0.001) were negatively associated with INSTI resistance at failure. In a large set of individuals failing dolutegravir in real-life, INSTI resistance was low and mainly related to previous first-generation INSTI exposure. Surveillance of integrase resistance remains crucial to preserve efficacy of INSTI class in the future.

The SARS-CoV-2 neutralizing antibodies response is the best indicator of effective protection after infection and/or vaccination, but its evaluation requires tedious cell-based experiments using an infectious virus. We analyzed, in 105 patients with various histories of SARS-CoV-2 infection and/or vaccination, the neutralizing response using a virus neutralization test (VNT) against B.1, Alpha, Beta and Omicron variants, and compared the results with two surrogate assays based on antibody-mediated blockage of the ACE2-RBD interaction (Lateral Flow Boditech and ELISA Genscript). The strongest response was observed for recovered COVID-19 patients receiving one vaccine dose. Naïve patients receiving 2 doses of mRNA vaccine also demonstrate high neutralization titers against B.1, Alpha and Beta variants, but only 34.3% displayed a neutralization activity against the Omicron variant. On the other hand, non-infected patients with half vaccination schedules displayed a weak and inconstant activity against all isolates. Non-vaccinated COVID-19 patients kept a neutralizing activity against B.1 and Alpha up to 12 months after recovery but a decreased activity against Beta and Omicron. Both surrogate assays displayed a good correlation with the VNT. However, an adaptation of the cut-off positivity was necessary, especially for the most resistant Beta and Omicron variants. We validated two simple and reliable surrogate neutralization assays, which may favorably replace cell-based methods, allowing functional analysis on a larger scale.

Previous reports have shown a variability in the diagnostic performance of RDTs. In the era of SARS-CoV-2 variants and the use of RDT, mutation associated with these variants could affect the test performance.

Comparing survival functions with the log‐rank test in the presence of dependent censoring can produce an invalid test result. We extend our previous work on the estimation of the survival function using prognostic variables to adjust for dependent censoring to the comparison of two survival distributions. In these estimators, the weights of a censored individual is redistributed among either a subset of patients in the risk set or all patients in the risk set but giving more weight to patients having smallest distances from the censored subject. The distance is based on two risk scores obtained from two working models, one for the failure time and one for the censoring time. Based on the estimators, we suggest a weighted log‐rank test to compare two survival distributions. A simulation study compared performance of our method with the analysis of the observed data without using auxiliary variables and with a recent method based on multiple imputation (KMIB method). With appropriate parameters, the weighted log‐rank approach provides sizes of the test comparable to the nominal value but higher powers than the two other methods. The method is illustrated with data from a breast cancer study.

The test of Yang and Prentice, based on the short-term and long-term hazard ratio model for the presence of a regression effect appears to be an attractive one, being able to detect departures from a null hypothesis of no effect against quite broad alternatives. We recall the model on which this test is based and the test itself. In simulations, the test has shown good performance and is judged to be of potential value when alternatives to the null may be of a nonproportional hazards nature. However, the model, even when valid, suffers from a parameterization inconsistency in the sense that parameter estimates can violate the model's assumed parametric structure even when true. This leads to awkward behavior in some situations. For example, this inconsistency implies that inference will not be invariant to the coding of treatment allocation. While this is a theoretical observation, we provide real examples that highlight the difficulty in making clear cut inferences from the model. Potential solutions are available and we provide some discussion on this.

Measuring the magnitude of reduction in HIV‐1 RNA levels accurately is difficult because many patients have a censored reduction due to the limit of detection (LOD) of the virologic assay being employed. The use of censored methods has improved the analysis of such reductions compared with crude methods but implies independent censoring. For HIV‐1 RNA reduction data, the value at which a patient's HIV‐1 RNA reduction becomes censored is mainly determined by the patient's baseline HIV‐1 RNA level. We suggest two possibilities based on modification of the redistribution to the right algorithm to handle the situation of dependence either from a single continuous marker, that is, the baseline HIV‐1 RNA level, or from multiple markers. Two series of simulation, one in the HIV‐1 RNA setting and one in the classical censoring setting, compared performance of the previous methods with our suggestions. Our proposed estimators show good performances when the dependent censoring is due to LOD. Overall, in the classical censoring setting, our suggestions perform as well as other methods including the Inverse Probability of Censoring Weighted and the Kaplan‐Meier imputation with Bootstrap. We applied those estimators to estimate the HIV‐1 RNA reduction at week 8 of 502 patients who received a raltegravir‐containing regimen and to data from the Mayo Clinic trial in primary biliary cirrhosis.