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Purpose <p>To quantify virologic failure (VF), identify predictors, characterize resistance patterns at failure, and evaluate time to resuppression in the RESINA cohort.</p> Methods <p>ART-naïve adults initiating ART in 2001–2024 were followed. VF was defined as at least one HIV-1 RNA &gt; 200 copies/mL after suppression or ≥ 0.5-log₁₀ rebound. Participants were grouped by treatment era (2001–2007, 2008–2013, ≥ 2014), reflecting availability of drug classes. Genotypes at baseline and VF were interpreted using the HIV-GRADE algorithm. Predictors of VF were assessed with logistic regression; time to resuppression (&lt; 50 copies/mL) after first VF with Cox models and Kaplan–Meier plots.</p> Results <p>Among 5136 participants, 139 (2.7%) had VF; rates declined across eras (4.7%, 2.6%, 1.7%). Independent predictors were injection-drug use (OR 1.74), CD4 &lt; 200/µL (OR 2.32), and ART start in 2001–2007 (OR 1.95); MSM acquisition was protective (OR 0.32). At failure, 36 patients showed resistance, often multiclass (61%); INSTI resistance was rare (n = 5). After first VF, 122/139 cases resuppressed (median 147&#xa0;days). Male sex predicted faster resuppression (HR 1.81); higher failure VL trended to slower resuppression (HR 0.84 per log₁₀). INSTI-based switches consistently achieved resuppression in descriptive analyses and were not associated with multiclass resistance.</p> Conclusion <p>VF was uncommon and declined over time, reflecting improved regimen potency and tolerability. Failures were associated with late presentation and IDU, consistent with adherence barriers. Resistance often involved multiple classes, while INSTI resistance remained infrequent. Early, genotype-guided optimization, preferably to INSTI-based therapy, combined with targeted adherence support may improve outcomes.</p>

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HIV-1 virologic failure in the RESINA cohort: lessons from two decades of real-world data

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月17日

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  • Smaranda Gliga,
  • Micha Böhm,
  • Nadine Lübke,
  • Alexander Killer,
  • Falk Hüttig,
  • Lila Haberl,
  • Jörg Timm,
  • Claudia Müller,
  • Eva Heger,
  • Joachim Büch,
  • Gerd Fätkenheuer,
  • Clara Lehmann,
  • Mark Oette,
  • Martin Hower,
  • Heribert Knechten,
  • Niels Schübel,
  • Stefan Esser,
  • Stephan Schneeweiß,
  • Nazifa Qurishi,
  • Katja Römer,
  • Jürgen K. Rockstroh,
  • Rolf Kaiser,
  • Tom Luedde,
  • Björn-Erik Ole Jensen

摘要

Purpose

To quantify virologic failure (VF), identify predictors, characterize resistance patterns at failure, and evaluate time to resuppression in the RESINA cohort.

Methods

ART-naïve adults initiating ART in 2001–2024 were followed. VF was defined as at least one HIV-1 RNA > 200 copies/mL after suppression or ≥ 0.5-log₁₀ rebound. Participants were grouped by treatment era (2001–2007, 2008–2013, ≥ 2014), reflecting availability of drug classes. Genotypes at baseline and VF were interpreted using the HIV-GRADE algorithm. Predictors of VF were assessed with logistic regression; time to resuppression (< 50 copies/mL) after first VF with Cox models and Kaplan–Meier plots.

Results

Among 5136 participants, 139 (2.7%) had VF; rates declined across eras (4.7%, 2.6%, 1.7%). Independent predictors were injection-drug use (OR 1.74), CD4 < 200/µL (OR 2.32), and ART start in 2001–2007 (OR 1.95); MSM acquisition was protective (OR 0.32). At failure, 36 patients showed resistance, often multiclass (61%); INSTI resistance was rare (n = 5). After first VF, 122/139 cases resuppressed (median 147 days). Male sex predicted faster resuppression (HR 1.81); higher failure VL trended to slower resuppression (HR 0.84 per log₁₀). INSTI-based switches consistently achieved resuppression in descriptive analyses and were not associated with multiclass resistance.

Conclusion

VF was uncommon and declined over time, reflecting improved regimen potency and tolerability. Failures were associated with late presentation and IDU, consistent with adherence barriers. Resistance often involved multiple classes, while INSTI resistance remained infrequent. Early, genotype-guided optimization, preferably to INSTI-based therapy, combined with targeted adherence support may improve outcomes.