| Literature DB >> 35114968 |
Ruojing Bai1, Shiyun Lv1, Hao Wu2, Lili Dai3.
Abstract
BACKGROUND: Global antiretroviral therapy has entered a new era. Integrase strand transfer inhibitor (INSTI) has become the first choice in acquired immunodeficiency syndrome (AIDS) treatment. Because INSTI has high antiviral efficacy, rapid virus inhibition, and good tolerance. However, INSTIs may increase the risk of obesity. Each INSTI has its unique impact on weight gain in patients with human immunodeficiency virus (HIV)/AIDS. This study systematically assessed different INSTIs in causing significant weight gain in HIV/AIDS patients by integrating data from relevant literature.Entities:
Keywords: Body weight; HIV/AIDS; Integrase inhibitors; Network meta-analysis
Mesh:
Substances:
Year: 2022 PMID: 35114968 PMCID: PMC8811997 DOI: 10.1186/s12879-022-07091-1
Source DB: PubMed Journal: BMC Infect Dis ISSN: 1471-2334 Impact factor: 3.090
Fig. 1Literature search flow chart
Basic characteristics and quality evaluation of the included studies
| Author | Year | Country | Type of study | Sex (M/F) | Ages | Sample sizes | Interventions | NOS/Jadad Scores |
|---|---|---|---|---|---|---|---|---|
| Leonardo Calza [ | 2019 | Italy | Cohort study | 138/58 | 43.1 ± 15.2 | 196 | RAL | 6 |
| 115/59 | 41.6 ± 12.8 | 174 | DTG | |||||
| 109/49 | 42.5 ± 13.6 | 158 | EVG | |||||
| Peter [ | 2020 | USA | Cohort study | 917/164 | 44(33–52) | 1081 | RAL | 7 |
| 2058/257 | 34(27–45) | 2315 | EVG | |||||
| 1044/166 | 35(28–48) | 1210 | DTG | |||||
| Kassem Bourgi [ | 2020 | USA | Cohort study | NA | NA | 63 | RAL | 5 |
| NA | NA | 153 | EVG | |||||
| NA | NA | 135 | DTG | |||||
| Kassem Bourgi [ | 2020 | USA | Cohort study | 1016/176 | NA | 1192 | RAL | 7 |
| 795/131 | NA | 926 | DTG | |||||
| 1842/226 | NA | 2068 | EVG | |||||
| Sax [ | 2020 | USA | RCT | 565/74 | 37 ± 11.9 | 639 | DTG | 4 |
| 434/67 | 38 ± 9.5 | 501 | BIC | |||||
| 567/62 | 34 ± 10.8 | 629 | EVG | |||||
| David A Wohl [ | 2019 | USA | RCT | 282/33 | 35(26–40) | 315 | DTG | 4 |
| 285/29 | 31(25–41) | 314 | BIC | |||||
| Stellbrink [ | 2019 | Germany | RCT | 280/40 | 33(27–46) | 320 | BIC | 6 |
| 288/37 | 34(27–46) | 325 | DTG | |||||
| Lake [ | 2020 | USA | Cohort study | NA | NA | 198 | DTG | 5 |
| NA | NA | 204 | EVG | |||||
| NA | NA | 289 | RAL |
NA not available; F female; M male; RCT randomized controlled trial
Fig. 2Network evidence diagram
Results of a network Meta-analysis of weight gain in patients with HIV/AIDS (MD, 95% CI)
| BIC | |||
|---|---|---|---|
| 0.06 (− 1.15, 1.27) | DTG | ||
| 1.19 (− 0.22, 2.60) | 1.13 (0.18, 2.07) | EVG | |
| 0.80 (− 0.70, 2.29) | 0.73 (− 0.22, 1.69) | − 0.39 (− 1.42, 0.63) | RAL |
Fig. 3Probability ranking of each drug to increase body weight in HIV/AIDS patients (SUCRA)
Node analysis of direct and indirect comparisons among interventions
| Category | Direct | Indirect | Difference | P | |||
|---|---|---|---|---|---|---|---|
| Coef | 95% CI | Coef | 95% CI | Coef | 95% CI | ||
| BIC vs DTG | − 0.162 | (− 1.47,1.15) | 1.105 | (− 3.40,5.61) | − 1.267 | (− 5.96,3.43) | 0.597 |
| BIC vs EVG | − 0.76 | (− 3.03,1.51) | − 1.504 | (− 3.43,0.43) | 0.744 | (− 2.24,3.73) | 0.625 |
| DTG vs EVG | − 1.16 | (− 2.19,-0.13) | − 0.752 | (− 4.34,2.83) | − 0.408 | (− 4.14,3.32) | 0.831 |
| DTG vs RAL | − 0.795 | (− 1.82,0.23) | 0.472 | (− 4.11,5.05) | − 1.267 | (− 5.96,3.43) | 0.597 |
| EVG vs RAL | 0.463 | (− 0.69,1.61) | − 0.113 | (− 3.20,2.97) | 0.576 | (− 2.72,3.87) | 0.732 |
Coef coefficient; 95% CI 95% confidence interval