Adherence Monitoring Methods to Measure Virological Failure in People Living with HIV on Long-Term Antiretroviral Therapy in Uganda

1 1 Adherence Monitoring Methods to Measure Virological 2 Failure in People Living with HIV on Long-Term 3 Antiretroviral Therapy in Uganda 4 5 Stephen Okoboi 1, Joseph Musaazi 1, Rachel King 2,3, Sheri A. Lippman 4, Andrew 6 Kambugu1, Andrew Mujugira 1,3, Jonathan Izudi 1, Rosalind Parkes-Ratanshi1,5, Agnes N. 7 Kiragga1, and Barbara Castelnuovo1 8 9 Institutional affiliation 10 1) Infectious Diseases Institute, Department of Medicine, Makerere University 11 College of Health Sciences. 12 2) Department of Global Health, University of California, San Francisco, San 13 Francisco, CA, United States. 14 3) School of Public Health, Makerere University, Kampala, Uganda. 15 4) Division of Prevention Science, Department of Medicine, University of California, 16 San Francisco, San Francisco, CA, United States. 17 5) Clinical School, University of Cambridge, United Kingdom 18 19 Corresponding author 20 Stephen Okoboi 21 Infectious Diseases Institute, College of Health Sciences, Makerere University 22 [email protected] / [email protected] . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. 2 23 Co-authors 24 25 JM: Joseph Musaazi; RK: Rachel King; SL: Sheri Lippman; AK: Andrew Kambugu; AM: 26 Andrew Mujugira; JI: Jonathan Izudi; RP: Rosalind Parkes-Ratanshi; ANK: Agnes N 27 Kiragga, and BC: Barbara Castelnuovo 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 3 48 Abstract 49 Appointment keeping and self-report within 7-day or and 30-days recall periods are non- 50 objective measures of antiretroviral treatment (ART) adherence. We assessed incidence 51 of virological failure (VF), predictive performance and associations of these adherence 52 measures with VF among adults on long-term ART. Data for persons initiated on ART 53 between April 2004 and April 2005, enrolled in a long-term ART cohort at 10-years on 54 ART (baseline) and followed until December 2021 was analyzed. VF was defined as two 55 consecutives viral loads ≥1000 copies/ml at least within 3-months after enhanced 56 adherence counselling. We estimated VF incidence using Kaplan-Meier and Cox- 57 proportional hazards regression for associations between each adherence measure 58 (analyzed as time-dependent annual values) and VF. The predictive performance of 59 appointment keeping and self-reporting for identifying VF was assessed using receiver 60 operating characteristic curves and reported as area under the curve (AUC). We included 61 900 of 1,000 participants without VF at baseline: median age was 47 years (Interquartile 62 range: 41-51), 60% were women and 88% were virally suppressed. ART adherence was 63 ≥95% for all three adherence measures. Twenty-one VF cases were observed with an 64 incidence rate of 4.37 per 1000 person-years and incidence risk of 2.4% (95% CI: 1.6%- 65 3.7%) over the 5-years of follow-up. Only 30-day self-report measure was associated with 66 lower risk of VF, adjusted hazard ratio (aHR)=0.14, 95% CI:0.05–0.37). Baseline CD4 67 count ≥200cells/ml was associated with lower VF for all adherence measures. The 30- 68 day self-report measure demonstrated the highest predictive performance for VF 69 (AUC=0.751) compared to appointment keeping (AUC=0.674), and 7-day self-report 70 (AUC=0.687). The incidence of virological failure in this study cohort was low. Whilst 30- . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 4 71 day self-report was predictive, appointment keeping and 7-day self-reported adherence 72 measures had low predictive performance in identifying VF. Viral load monitoring remains 73 the gold standard for adherence monitoring and confirming HIV treatment response. 74 75 Keywords: Anti-retroviral Therapy, Long-term ART, Adherence, Self-report, Virological 76 failure 77 Word counts: 298 abstracts 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 5 95 Introduction 96 The WHO public health approach for scaling up access to anti-retroviral therapy (ART) 97 expanded following the availability of highly active anti-retroviral medication through 98 standardized regimes and decentralized care in Low and Middle Income Countries (LMIC) 99 (1). In this approach, standardized simplified ART regimens and decentralized treatment 100 delivery enabled large numbers of people with HIV (PHW) to be initiated and followed-up 101 on treatment through public and private sector health facilities. The approach is centred 102 on “four Ss”, an acronym for when to Start drug treatment, Substitute for toxicity, Switch 103 after treatment failure, and Stop to enable lower-level healthcare workers to deliver 104 appropriate care (1). 105 In 2020, an estimated 17 million people were on ART in sub-Saharan Africa (SSA) (2); 106 in Uganda, 1,275,000 million persons were estimated to be on ART in 2019 (3). The 2018 107 and 2020 HIV treatment guidelines in Uganda recommend ART adherence monitoring 108 using non-objective measures including pill counts, appointment keeping, visual analogue 109 scales, and self-reported pill use, used either individually or in combination (4,5). The use 110 of these adherence measures encourages ART adherence discussions with patients and 111 providing information about the risk of virological failure or to support daily tablet-taking 112 behavior in settings where viral load testing is limited (6–8). However, in 2016, the Uganda 113 Ministry of Health (MoH) HIV treatment guidelines recommended annual plasma HIV viral 114 load for people on ART to monitor treatment effectiveness and identify individuals with 115 detectable viral load (9). Annual viral load monitoring is recommended due to scarcity of 116 resources in LMIC (10,11). . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 6 117 Sustained optimal adherence to ART ensures virological suppression, reduction in HIV- 118 related morbidity and mortality, and prevents onward transmission (6,12,13), popularized 119 by the Joint United Nations Programme on HIV/AIDS (UNAIDS) as “Undetectable equals 120 Untransmittable (U=U) (14,15). However, previous studies report discrepancies in ART 121 adherence thresholds used. And adherence measured as a categorical or a continuous 122 constructs from patients or clinic reports affecting association and predictive performance 123 between ART adherence measures and virological failure among PWH on ART (6,7,16– 124 18). The performance of ART adherence measures in predicting virological failure among 125 adult PWH on long-term ART (i.e., ≥10 consecutive years of ART use), including the 126 predictors for virological failure are not well described across ART programs in LMIC. 127 Despite self-reporting being routinely used as an adherence proxy in clinical care, few 128 studies have evaluated the incidence of virological failure, predictive performance, and 129 associations of appointment keeping, self-report within 7-day or and 30-days recall 130 periods with VF among adults on long-term ART. 131 132 Thus, this study aimed to describe the incidence of virological failure, compare the 133 predictive performance of three ART adherence measures (7-days and 30-days self- 134 reported pill use, and appointment keeping) and assess factors associated with virological 135 failure among PWH on long-term first-line ART. 136 137 138 139 140 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 7 141 Methods 142 Study design and setting 143 This study was conducted at the HIV Centre of Excellence at the Infectious Diseases 144 Institute (IDI) located in the Mulago Teaching Hospital in Kampala, the capital city of 145 Uganda. The IDI clinic is a large out-patient clinic that currently serves over 8,000 patients 146 living with HIV in five municipalities in Kampala. 147 This was a secondary analysis of a longitudinal cohort data of patients enrolled in the 148 Long-Term ART cohort. The ART Long-Term cohort is an observational cohort of 1,000 149 patients who had been on ART for at least 10 years and were enrolled between May 2014 150 and September 2015 to be followed up for an additional 10 years (19). Patients were 151 eligible and enrolled in the cohort if they were ≥18-years, were willing to participate in the 152 cohort visits and comply with the study procedures, and were in their 10th consecutive 153 year of WHO standard ART at IDI regardless of the combination of drugs for first-line 154 ART. Ten-year consecutive ART use was determined using data collected in the IDI 155 electronic database, known as the Integrated Clinic Enterprise Application (ICEA). This is 156 an in-house built system based on Microsoft.NET technologies (19). This interim analysis 157 describes the first five years of follow-up. 158 159 Data Collection 160 General medical history, physical examination, adherence to ART, and prescription of 161 drugs were performed at enrolment and all study visits. Follow-up visits were scheduled 162 once a year for 10-years. In addition to study visits, the participants attended the general . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 8 163 clinic every 3-months to pick up their ART and concomitant medications. Antiretroviral 164 drugs are prescribed according to the WHO guidelines; patients with two consecutive viral 165 loads >1000 copies/ml after enhanced adherence counselling are considered for 166 treatment switch. Enhanced adherence counselling is a targeted counselling offered to 167 PWH on ART with non-suppressed viral load, done every month for at least 3-months 168 before the next viral load test (5). At each study visit, real-time data entry into ICEA is 169 performed by the respective providers (19). Laboratory results performed in the IDI Core 170 Laboratory are automatically downloaded daily into the ICEA database. The 171 questionnaires administered at each visit include basic demographic and epidemiological 172 data, clinical history, adherence to ART, quality of life, and sexual behavior. Clinical data 173 collected at each visit included vital signs and body weight, hematological and chemistry 174 laboratory results, medications and ART regimen, and drug toxicities. All the data 175 collected into ICEA are validated by a quality control and assurance officer who ensures 176 that the data are complete and consistent. 177 178 Adherence Measures 179 The primary outcome was virological failure defined as two consecutive plasma HIV RNA 180 viral load measurements ≥1000 copies/ml at least within 3-months after receiving 181 enhanced adherence counselling following the first viral load measurement. The 182 exposure was ART adherence assessed using 3 different measures: self-reported pill use 183 in the last 7 days, self-reported pill use in the last 30 days, and appointment keeping. The 184 30-day and 7-day self-report of pill use ART adherence measure was assessed on a scale 185 of 1-100 by asking the patient to recall the numbers of missed doses in the last 30-days . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 9 186 and 7-days and then calculating, what percentage of ART doses were taken. Good 187 adherence was determined as having a score ≥95%. Appointment keeping was defined 188 as returning for a scheduled cohort clinic visit appointment or within a 7-day window after 189 a missed clinic visit. Questions were assessed throughout the entire 5-year follow-up 190 period. Additional co-variates included age, sex, marital status, employment status, HIV 191 disclosure status, household level of income, and body mass index. 192 193 We extracted cohort data from 10 to 15 years on ART follow-up (or enrollment in the 194 cohort and five years of follow-up). When the required data were missing, patient charts 195 were retrieved and reviewed to supplement the data in the databases. We extracted 196 clinical data including ART start dates and regimens, socio-demographics at cohort 197 enrolment, behavioral data, CD4 cell counts, plasma HIV viral load measurements for the 198 follow-up period using or Roche COBAS® Ampli Prep. We also extracted data on deaths, 199 transferred out, and lost to follow-up. 200 201 Statistical analysis 202 Statistical analysis was performed using STATA 16.1 (StataCorp, College Station, Texas). 203 We described cohort participants using frequencies and percentages for categorical 204 variables and continuous variables using means and standard deviations and medians 205 and interquartile ranges. Adherence measures were described using frequency and 206 percentages across calendar year. Kaplan-Meier methods were used to estimate 207 incidence risk and incidence rate of virological failure. Associations between virological 208 failure and ART adherence was examined using Cox-proportional hazards regression . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 10 209 (Cox-PH) models. ART adherence measures were entered into the model as time- 210 dependent covariates measured at annual cohort visits. The Schoenfeld residuals test 211 was used to assess for violation of the Cox –PH assumption. Three sensitivity analyses 212 were performed, by refitting the model when: 1) missing values on covariates were 213 imputed by multiple imputation using chained equations (MICE), 2) considering all 214 censored patients i.e., deaths and losses to follow-up as virological failure (worst-case 215 scenario), and 3) when considered as non-virological failure (best-case scenario). 216 Performance of ART adherence measures - appointment keeping, 30-days and 7-days 217 self-report of pill use for predicting virological failure was evaluated using receiver 218 operating characteristic curve analysis. All hypothesis tests were performed as 2-tailed 219 tests at a 5% significance level. 220 221 Ethical approval 222 This study was approved by the Infectious Diseases Institute Research Ethics Committee 223 (reference number; IDI REC-041/2021) and the Uganda National Council for Science and 224 Technology (reference number; HS1896ES). The IDIREC committee granted a waiver of 225 informed consent since secondary data were retrieved and analysed. 226 227 228 229 230 231 232 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 11 233 Results 234 Study Profile 235 We retrieved data for 1,000 PWH adults enrolled in the long-term ART cohort who started 236 ART between April 2004 and April 2005 and were followed up until December 2021. Of 237 the 1,000 participants, 100 (10%) had a viral load (VL) >1000 copies/ml documented at 238 cohort enrolment and were therefore excluded from the study. Nine hundred participants 239 were included in the analysis, of whom 10 had transferred to other health facilities, 45 240 were lost to follow-up and 41 had died before reaching 15 years on ART (Fig 1). 241 Participant characteristics 242 Participants’ description 243 Of the 900 cohort participants analyzed, at cohort enrollment: the median age was 46 244 years (IQR 41- 51); 59.8% were females, 82.1% were employed, 43.9% lived <1 US dollar 245 per day, median body mass index (BMI) was 22.4 (IQR 19.8-25.4), 51.3% were married 246 or cohabiting, and 88.4% had viral load <50 copies/ml (10 years on ART), (Table 1). 247 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 12 248 Table 1: Baseline characteristics (at 10 years on ART) Variables Statistics N=900 Sex Male 362 (40.2) Female 538 (59.8) Age (years) at cohort 2 registration Median (IQR) 46.0 (41.0, 51.0) Age categories 28-44 388 (43.1%) 45-54 368 (40.9%) ≥55 144 (16.0%) BMI at baseline (cohort registration) Median (IQR) 22.4 (19.8, 25.4) BMI <18kg/m2, N (%) 108 (12.6) VL at cohort 2registration (c/ml) Median (IQR) 20.0 (20.0, 20.0) Baseline VL categories (copies/ml), N (%) <50 635 (88.4) ≥50 83 (11.6) CD4 at cohort2registration (cells/ml) Median (IQR) 491.0 (347.0, 662.0) CD4 <200 cells/ml, N (%) 36 (4.4) Marital status, N (%) Single/Separated/Divorced/Widowed 438 (48.7) Married/Cohabiting 462 (51.3) Employed, N (%) No 160 (17.9) Yes 735 (82.1) Household monthly income (as <30$ vs ≥30$), N (%) <30$ per month 374 (43.9) ≥30$ per month 477 (56.1) Disclosure status, N (%) No 830 (92.2) Yes 70 (7.8) 249 Table 1 footnote: SD denotes standard deviation, IQR interquartile range, BMI body mass 250 index. Missing values: BMI (n=42, 5%), Baseline VL (n=182, n=20%), CD4 count (n=81, 9%), 251 employed (n=5, 0.6%), household monthly income (n=49, 5%) . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 13 252 The virological failure incidence rate was 4.37 (95% CI: 2.85 - 6.70) per 1000 person- 253 years and the probability of virological failure was 2.4%, (95% CI: 1.6% - 3.7%) over 15 254 years, (Fig 2). ART adherence was very high (≥95%) over the 7-calendar years studied 255 on all adherence measures, except appointment keeping declined in 2019 and 2020 256 (42.0% and 72.7%, respectively) (Table 2). 257 Table 2: ART Adherence measures (self-reported and appointment keeping 258 during 2014 – 2020 2014 2015 2016 2017 2018 2019 2020 (N = 137) (N = 375) (N = 968) (N = 960) (N = 940) (N = 896) (N = 343) 7-day self-reported adherence No 4 (2.9%) 9 (2.4%) 38 (3.9%) 28 (2.9%) 18 (1.9%) 9 (1.0%) 5 (1.5%) Yes 133 (97.1%) 366 (97.6%) 929 (96.1%) 931 (97.1%) 922 (98.1%) 885 (99.0%) 329 (98.5%) 30-day self-reported adherence score ≥95%) No 1 (0.7%) 1 (0.3%) 241 (26.1%) 180 (18.8%) 72 (7.7%) 38 (4.3%) 8 (2.5%) Yes 135 (99.3%) 373 (99.7%) 682 (73.9%) 776 (81.2%) 864 (92.3%) 851 (95.7%) 313 (97.5%) Appointment keeping adherence measure No 5 (3.6%) 23 (6.2%) 65 (6.8%) 46 (4.9%) 64 (7.0%) 403 (58.0%) 83 (27.3%) Yes 132 (96.4%) 346 (93.8%) 891 (93.2%) 896 (95.1%) 849 (93.0%) 292 (42.0%) 221 (72.7%) 259 Missing data: Self-reported (0,0,1,1,0,2,9 for 2014, 2015, 2016, 2017, 2018, 2019, 2020 respectively), Appointment 260 keeping (0,6,12,18,27,201,39 for 2014, 2015, 2016, 2017, 2018, 2019, 2020 respectively), VAS (1,1,45,4,4,7,22 for 261 2014, 2015, 2016, 2017, 2018, 2019, 2020 respectively) 262 263 Associations between virologic failure and ART adherence measures 264 Table 3 shows that after adjusting for other patient factors, ART adherence assessed 265 using 30-day self-report was associated with lower risk of virological failure (adjusted 266 hazard ratio [AHR] 0.14; 95% CI: 0.05 - 1.76). However, the relationship was not 267 significant when ART adherence was measured using 7-day self-report or appointment 268 keeping (AHR 0.36; 95% CI: 0.05 – 2.75 and AHR 2.27; 95% CI: 0.27–18.83), 269 respectively. Among other patient factors, only baseline CD4 ≥200 cells/ml was . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 14 270 associated with lower risk of virological failure in models including all three adherence 271 measures: 30-day self-report (AHR 0.24; 95% CI: 0.07–0.85), 7-day self-report (AHR 272 0.26; 95% CI: 0.08 – 0.91) and appointment keeping (AHR 0.22; 95% CI: 0.06 – 0.76). 273 In sensitivity analyses, when imputing missing covariate data, the association between 274 adherence and virological failure only remained for 30-day ART self-report (AHR 0.14; 275 95% CI: 0.05 – 0.35). There was no significant association with 7-day self-reported or 276 appointment keeping measures (Supplementary tables). 277 278 279 280 281 282 283 284 285 286 287 288 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 15 289 Table 3: Associations of ART adherence and virologic failure, adjusting for 290 baseline and time-dependent patient characteristics 291 292 Footnote: ART adherence modelled as time-dependent covariates in all models. Analysis performed on complete 293 cases for all covariates adjusted in the model: 11% (100/900) missing in model 1 and 2, whereas 12% (105/900) missing 294 in model 3. aHR denotes adjusted hazard ratio from Cox proportional hazard regression models, CI denotes confidence 295 interval. Apart from adherence (the main exposure), in the adjusted models we Included only covariates with P 296 value0.2 in 297 unadjusted Cox models, and thus were excluded from adjusted models. 298 299 Adherence predictive performance of virologic failure 300 In the receiver operating characteristics curve (ROC) analysis for predictivity ability of 301 adherence measures for virological failure, 30-day self-report best predicted virological 302 failure (area under the curve [AUC] 0.751; 95% CI: 0.66 - 0.90) versus appointment 303 keeping (AUC 0.674; 95% CI: 0.53 - 0. 81) and 7-day self-report (AUC 0.687; 95% CI: 304 0.51-0.82) (Fig 3). Factor Model 1 30-day self-report ART adherence measure (as main exposure) (n=800) Model 2 7-day self-report ART adherence measure (as main exposure) (n=800) Model 3 ART adherence measure Appointment keeping (as main exposure) (n=795) ART adherence (time-updated) aHR (95% CI) P value aHR (95% CI) P value aHR (95% CI) P value Non-adherent 1 1 1 Adherent 0.14 (0.05 – 0.37) <0.001 0.36 (0.05 – 2.75) 0.325 2.27 (0.27 – 18.83) 0.447 Other factors adjusted Sex Male 1 1 1 Female 2.29 (0.74 – 7.07) 0.149 2.46 (0.81 – 7.50) 0.133 2.84 (0.80 – 10.06) 0.106 CD4 count at cohort registration (cells/mL) <200 1 1 1 ≥200 0.24 (0.07 – 0.85) 0.027 0.26 (0.08 – 0.91) 0.035 0.22 (0.06 – 0.76) 0.017 Employment status Unemployed 1 1 1 Employed 0.57 (0.21 – 1.55) 0.275 0.57 (0.22 – 1.53) 0.267 0.60 (0.21 – 1.76) 0.353 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 16 305 Discussion 306 Overall, we found that unlike 30-day self-report, appointment keeping and 7-day self- 307 reported adherence measures had low predictive performance in identifying virological 308 failure. We also found a low incidence of virological failure among person living with HIV 309 in this long-term ART study cohort. Our finding of low incidence of virological failure is 310 consistent with an observational cohort analysis conducted in Uganda at The AIDS 311 Support Organization among 3,340 persons who initiated ART from 2004 - 2009 and 312 followed-up for a median of 5.7 years (IQR, 4.1 - 7.2 years) which found a low rate of 313 virological failure among adult HIV patients on first-line antiretroviral therapy (20). Our 314 study reports a low incidence of virological failure comparable to 7.4% reported among 315 participants in the first Infectious Diseases Institute cohort followed up-to 10 years on 316 ART (21). The lower incidence of virological failure observed in our study could be 317 attributed to the longer duration on ART and the fixed dose once-daily therapy which was 318 introduced around the time of cohort enrollment (19,22,23). Participants on long-term 319 ART have received many ART adherence counselling sessions that should increase 320 awareness about the importance of ART adherence and possibly drug side effects (21, 321 22). Furthermore, this is a survivor cohort of persons who have been on ART for at least 322 ten years; there is evidence that shorter ART duration is conversely associated with 323 increased risk of virological failure (23). This is due to the recent policy of universal test 324 and treat, which increase the likelihood that patients with a new diagnosis of HIV tend to 325 be unprepared to start ART as they have had limited psychosocial support due to rapid 326 initiation (23,24). The issues of stigma, sero-status disclosure to people close to them . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 17 327 and discrimination is another concern among people on ART as it increases non- 328 adherence to treatment (23,24). 329 330 We found that baseline CD4 cells ≥200 cells/ml was associated with lower risk of 331 developing virological failure in models using each of the three adherences measures. 332 Our finding is similar to several studies both in developed and LMIC that have reported 333 low baseline CD4 count have increased risk of developing virological failure (26). This 334 finding is supported by other studies which recommended closer monitoring and ART 335 adherence counselling for persons who commence ART with low CD4 count (26,27). 336 337 We also found that all the three adherence measures had low predictive performance in 338 identifying virological failure. However, the 30-day self-report adherence measure was 339 most able to predict virological failure. Our finding that 30-day self-report predicted 340 virological failure is consistent with a study by Minyi et al., 2008 (28) who found that 1- 341 month self-report ART adherence was more accurate in measuring ART adherence and 342 predicating virological failure than 3-day or 7-day self-reported ART adherence (28–30). 343 Other studies conducted in sub-Saharan Africa have found that self-report adherence 344 measures have low predictive performance in detecting virological failure among 345 participants on long and short-term ART (29). This could be because each of these 346 adherence measures has inherent weakness such us their accuracy and precision due 347 to recall and social desirability in different settings (25). Therefore, viral load monitoring 348 as per WHO, remains the gold standard for identifying virological failure, monitoring ART . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 18 349 adherence, and confirming treatment failure among people on ART even if its scale-up in 350 resource-limited setting is hindered by financial and technical constraints (31). 351 352 To improve ART adherence, HIV care programs in LMIC should continue to educate 353 people living with HIV on the importance of reporting accurate and consistent ART 354 adherence, keeping dosing schedules, and explaining adverse effects. National ART 355 guidelines should pay particular attention to monitoring virological failure and supporting 356 ART adherence among persons who initiate ART with lower CD4 count. Monitoring viral 357 load helps identify PWH on ART who have sustained long-term viral load suppression 358 and is crucial in HIV prevention efforts given that national programs are promoting the 359 UNAIDS slogan of undetectable equals to untransmissible (U=U). As we disseminate and 360 implement the UNAIDS policy, programs should integrate objective methods of 361 measuring adherence like medication event monitoring systems, and biologic measures 362 like point of care tenofovir testing that best predict virological failure. 363 The key strength of our study is the prospective data collection design among long-term 364 ART persons, large sample size, long duration of follow-up, and objective ascertainment 365 of virological failure. However, our study has limitations. These findings may not be 366 generalizable because persons were from an HIV centre of excellence, which may not be 367 representative for smaller centres or primary care settings, social desirability bias, 368 immortal time bias could have affected the study findings. Also, this is a non-randomized 369 comparison and is subject to unmeasured confounding. Twenty percent of viral load data 370 were missing but we used multiple imputation in the sensitivity analysis. 371 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 19 372 Conclusion 373 The incidence of virological failure among PWA on long-term ART in this cohort study 374 was low. Unlike the 30-day self-report, appointment keeping and 7-day self-reported ART 375 adherence measures had low predictive performance in identifying virological failure. 376 Routine plasma viral load monitoring remains the gold standard for adherence monitoring 377 and confirming HIV treatment response. 378 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 20 379 Acknowledgements 380 This project was supported by the Fogarty International Center of the National Institutes 381 of Health (NIH) under Award Number D43TW009343 and the University of California 382 Global Health Institute (UCGHI). The content is solely the responsibility of the authors 383 and does not necessarily represent the official views of the NIH or UCGHI. BC was partly 384 supported by the Fogarty International Centre, National Institute of Health (grant# 385 2D43TW009771-06 “HIV and co-infections in Uganda"). 386 387 Declaration of conflicts of interest 388 The authors declare no conflict of interest 389 Author Contributions 390 Conceptualization: Stephen Okoboi, Barbara Castelnuovo, Rachel King 391 Data curation: Stephen Okoboi and Joseph Musaazi 392 Formal analysis: Stephen Okoboi, Joseph Musaazi, Izudi Jonathan, Sheri A. Lippman 393 Methodology: Stephen Okoboi, Joseph Musaazi, Rachel King, Sheri A. Lippman, 394 Andrew Kambugu, Andrew Mujugira, Jonathan Izudi, Rosalind Parkes-Ratanshi, Agnes 395 N. Kiragga, and Barbara Castelnuovo 396 Project administration: Stephen Okoboi 397 Supervision: Rachel King, Sheri A. Lippman and Barbara Castelnuovo . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 21 398 Review and approval: Stephen Okoboi, Joseph Musaazi, Rachel King, Sheri A. 399 Lippman, Andrew Kambugu, Andrew Mujugira, Jonathan Izudi, Rosalind Parkes- 400 Ratanshi, Agnes N. Kiragga, and Barbara Castelnuovo 401 402 References 403 1. Ford N, Ball A, Baggaley R, Vitoria M, Low-Beer D, Penazzato M, Vojnov L, 404 Bertagnolio S, Habiyambere V, Doherty M, Hirnschall G. The WHO public health 405 approach to HIV treatment and care: looking back and looking ahead. Lancet 406 Infect Dis. 2018 Mar;18(3):e76-e86. doi: 10.1016/S1473-3099(17)30482-6. Epub 407 2017 Oct 20. PMID: 29066132 408 2. UNAIDS. FACT SHEET 2021 Global HIV Statistics. End AIDS epidemic. 409 2021;(June):1–3. 410 3. Ministry of Health Uganda Population - Based HIV I Mpact a Ssessment. 2019;0– 411 252. 412 4. Ministry of Health-Uganda. Consolidated Guidelines for Prevention. 413 2016;(December). 414 5. Uganda Ministry of Health. Consolidated Guidelines on the prevention and 415 treatment of HIV. 2018;(September). 416 6. Sangeda RZ, Mosha F, Prosperi M, Aboud S, Vercauteren J, Camacho RJ, et al. 417 Pharmacy refill adherence outperforms self-reported methods in predicting HIV 418 therapy outcome in resource-limited settings. BMC Public Health. 2014;14(1):1– . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 22 419 11. 420 7. Aye WL, Puckpinyo A, Peltzer K. Non-adherence to anti-retroviral therapy among 421 HIV infected adults in Mon State of Myanmar. BMC Public Health. 2017;17(1):1– 422 10. 423 8. Mekuria LA, Nieuwkerk PT, Yalew AW, Sprangers MAG, Prins JM. High level of 424 virological suppression among HIVinfected adults receiving combination 425 antiretroviral therapy in Addis Ababa, Ethiopia. Antivir Ther. 2016;21(5):385–96. 426 9. Ministry of Health-Uganda. Consolidated Guidelines for the Prevention and 427 Treatment of HIV and AIDS in Uganda. Minist Heal Uganda [Internet]. 428 2020;(February):142–70. Available from: 429 https://uac.go.ug/sites/default/files/Consolidated HIV Guidelines 2020.pdf 430 10. Médecins Sans Frontières. How Low Can We Go? Pricing for HIV Viral Load 431 Testing in Low- and Middle-Income Countries. 2013;41(0):1–8. 432 11. Rouet F, Rouzioux C. HIV-1 viral load testing cost in developing countries: What’s 433 new? Expert Rev Mol Diagn. 2007;7(6):703–7. 434 12. Wu P, Johnson B, Nachega J, Wu B, Ordonez C, Hare A, et al. The Combination 435 of Pill Count and Self-Reported Adherence is a Strong Predictor of First-Line ART 436 Failure for Adults in South Africa. Curr HIV Res. 2014;12(5):366–75. 437 13. Kabore L, Muntner P, Chamot E, Zinski A, Burkholder G, Mugavero MJ. Self- 438 report measures in the assessment of antiretroviral medication adherence: 439 Comparison with medication possession ratio and HIV viral load. J Int Assoc . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 23 440 Provid AIDS Care. 2015;14(2):156–62. 441 14. Okoli C, Van De Velde N, Richman B, Allan B, Castellanos E, Young B, et al. 442 Undetectable equals untransmittable (U = U): Awareness and associations with 443 health outcomes among people living with HIV in 25 countries. Sex Transm Infect. 444 2021;97(1):18–26. 445 15. Bor J, Fischer C, Modi M, Richman B, Kinker C, King R, et al. Changing 446 Knowledge and Attitudes Towards HIV Treatment-as-Prevention and 447 “Undetectable = Untransmittable”: A Systematic Review. AIDS Behav [Internet]. 448 2021;(0123456789). : AIDS Behav. 2021 Dec;25(12):4209-4224 Available from: 449 https://doi.org/10.1007/s10461-021-03296-8 450 16. Haberer JE, Bwana BM, Orrell C, Asiimwe S, Amanyire G, Musinguzi N, et al. 451 Adherence in early versus late ART initiation in sub-Saharan Africa. Top Antivir 452 Med. 2018;26 (Supple:214s-215s. 453 17. Gare J, Kelly-Hanku A, Ryan CE, David M, Kaima P, Imara U, et al. Factors 454 influencing antiretroviral adherence and virological outcomes in people living with 455 HIV in the Highlands of Papua New Guinea. PLoS One. 2015;10(8). 456 18. Wu P, Johnson B, Nachega J, Wu B, Ordonez C, Hare A, et al. The Combination 457 of Pill Count and Self-Reported Adherence is a Strong Predictor of First-Line ART 458 Failure for Adults in South Africa. Curr HIV Res. 2014;12(5):366–75. 459 19. Castelnuovo B, Mubiru F, Kiragga AN, Musomba R, Mbabazi O, Gonza P, et al. 460 Antiretroviral treatment Long-Term (ALT) cohort: A prospective cohort of 10 years . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 24 461 of ART-experienced patients in Uganda. BMJ Open. 2018;8(2):1–8. 462 20. Okoboi S, Ding E, Persuad S, Wangisi J, Birungi J, Shurgold S, et al. Community- 463 based ART distribution system can effectively facilitate long-term program 464 retention and low-rates of death and virologic failure in rural Uganda. AIDS Res 465 Ther. 2015;12(1):37. 466 21. Castelnuovo B, Kiragga A, Musaazi J, Sempa J, Mubiru F, Wanyama J, et al. 467 Outcomes in a cohort of patients started on antiretroviral treatment and followed 468 up for a decade in an urban clinic in Uganda. PLoS One. 2015;10(12):1–11. 469 22. Bukenya D, Mayanja BN, Nakamanya S, Muhumuza R, Seeley J. What causes 470 non-adherence among some individuals on long term antiretroviral therapy? 471 Experiences of individuals with poor viral suppression in Uganda. AIDS Res Ther 472 [Internet]. 2019;16(1):1–9. Available from: https://doi.org/10.1186/s12981-018- 473 0214-y 474 23. Lippman SA, El Ayadi AM, Grignon JS, Puren A, Liegler T, Venter WDF, et al. 475 Improvements in the South African HIV care cascade: findings on 90-90-90 476 targets from successive population-representative surveys in North West 477 Province. J Int AIDS Soc. 2019;22(6). 478 24. Damulak PP, Ismail S, Manaf RA, Said SM, Agbaji O. Interventions to improve 479 adherence to antiretroviral therapy (Art) in sub-saharan africa: An updated 480 systematic review. Int J Environ Res Public Health. 2021;18(5):1–18. 481 25. Orrell C, Cohen K, Leisegang R, Bangsberg DR, Wood R, Maartens G. . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint 25 482 Comparison of six methods to estimate adherence in an ART-naïve cohort in a 483 resource-poor setting: Which best predicts virological and resistance outcomes? 484 AIDS Res Ther. 2017;14(1):1–11. 485 26. Leierer G, Grabmeier-Pfistershammer K, Steuer A, Sarcletti M, Geit M, Haas B, et 486 al. A single quantifiable viral load is predictive of virological failure in human 487 immunodeficiency virus (HIV)-infected patients on combination antiretroviral 488 therapy: The austrian HIV cohort study. Open Forum Infect Dis. 2016;3(2):1–9. 489 27. Doyle T, Smith C, Vitiello P, Cambiano V, Johnson M, Owen A, et al. Plasma HIV- 490 1 RNA detection below 50 copies/mL and risk of virologic rebound in patients 491 receiving highly active antiretroviral therapy. Clin Infect Dis. 2012;54(5):724–32. 492 28. Minyi, Safren SA, Skolnik PR, Rogers WH, Coady W, Hardy H, et al. Optimal 493 recall period and response task for self-reported HIV medication adherence. AIDS 494 Behav. 2008;12(1):86–94. 495 29. Finitsis DJ, Pellowski JA, Huedo-Medina TB, Fox MC, Kalichman SC. Visual 496 analogue scale (VAS) measurement of antiretroviral adherence in people living 497 with HIV (PLWH): a meta-analysis. J Behav Med. 2016 Dec;39(6):1043-1055. doi: 498 10.1007/s10865-016-9770-6. 499 31. World Health Organization. Updated recommendations on HIV prevention, infant 500 diagnosis, antiretroviral initiation and monitoring. 2021. 67 p. 501 . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint . CC-BY 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 17, 2022. ; https://doi.org/10.1101/2022.05.11.22274977doi: medRxiv preprint