METHODS: This cross-sectional study recruited adult PWH during routine follow-up at five HIV clinical sites in the Asia-Pacific region. Participants were screened for depression using Patient Health Questionnaire-9 and SU using Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST). Quality of life (QoL) was assessed with WHOQOL-HIV BREF and functional ability with World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0). Factors associated with mean QoL and disability scores were analysed using linear regression.
RESULTS: Of 864 PWH enrolled, 753 screened positive for depression or SU. The median (interquartile range, IQR) age was 38 (31-47) years and 97% were on ART. Overall mean WHOQOL-HIV BREF and WHODAS scores indicated greater impairment with increasing depressive symptom severity and SU risk. In multivariate analysis, PWH reporting previous trauma/stress (difference = 2.7, 95% confidence interval [CI] 1.5-3.9, P
METHODS: This study included people living with HIV enrolled in a longitudinal cohort study from 2003 to 2019, receiving antiretroviral therapy (ART), and without prior tuberculosis. BMI at ART initiation was categorized using Asian BMI classifications: underweight (<18.5 kg/m2 ), normal (18.5-22.9 kg/m2 ), overweight (23-24.9 kg/m2 ), and obese (≥25 kg/m2 ). High FBG was defined as a single post-ART FBG measurement ≥126 mg/dL. Factors associated with high FBG were analyzed using Cox regression models stratified by site.
RESULTS: A total of 3939 people living with HIV (63% male) were included. In total, 50% had a BMI in the normal weight range, 23% were underweight, 13% were overweight, and 14% were obese. Median age at ART initiation was 34 years (interquartile range 29-41). Overall, 8% had a high FBG, with an incidence rate of 1.14 per 100 person-years. Factors associated with an increased hazard of high FBG included being obese (≥25 kg/m2 ) compared with normal weight (hazard ratio [HR] = 1.79; 95% confidence interval [CI] 1.31-2.44; p 25 kg/m2 were at increased risk of high FBG. This indicates that regular assessments should be performed in those with high BMI, irrespective of the classification used.
METHODS: All PLWH enrolled in adult HIV cohorts of IeDEA Asia-Pacific who started with triple-ART with at least 1 CD4, CD8 (3-month window), and HIV-1 RNA measurement post-ART were included. CD4/CD8 ratio normalization was defined as a ratio ≥1. Longitudinal changes in CD4/CD8 ratio were analyzed by linear mixed model, the incidence of the normalization by Cox regression, and the differences in ratio recovery by group-based trajectory modeling.
RESULTS: A total of 5529 PLWH were included; 80% male, median age 35 years (interquartile range [IQR], 29-43). First-line regimens were comprised of 65% NNRTI, 19% PI, and 16% INSTI. The baseline CD4/CD8 ratio was 0.19 (IQR, 0.09-0.33). PLWH starting with NNRTI- (P = 0.005) or PI-based ART (P = 0.030) had lower CD4/CD8 recovery over 5 years compared with INSTI. During 24,304 person-years of follow-up, 32% had CD4/CD8 ratio normalization. After adjusting for age, sex, baseline CD4, HIV-1 RNA, HCV, and year of ART initiation, PLWH started with INSTI had higher odds of achieving CD4/CD8 ratio normalization than NNRTI- (P < 0.001) or PI-based ART (P = 0.015). In group-based trajectory modeling analysis, INSTI was associated with greater odds of being in the higher ratio trajectory.
CONCLUSIONS: INSTI use was associated with higher rates of CD4/CD8 ratio recovery and normalization in our cohort. These results emphasize the relative benefits of INSTI-based ART for immune restoration.
METHODS: We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry.
RESULTS: In European ancestry samples, 14 genes were significantly associated (q
METHODS: A total of 12,901 breast cancer cases and 12,583 controls from 12 case-control studies were included in our pooled analysis. HLA imputation was performed using SNP2HLA on 10,886 quality-controlled variants within the 15-55 Mb region on chromosome 6. HLA alleles (n = 175) with info scores greater than 0.8 and frequencies greater than 0.01 were included (resolution at two-digit level: 71; four-digit level: 104). We studied the associations between HLA alleles and breast cancer risk using logistic regression, adjusting for population structure and age. Associations between HLA alleles and the risk of subtypes of breast cancer (ER-positive, ER-negative, HER2-positive, HER2-negative, early-stage, and late-stage) were examined.
RESULTS: We did not observe associations between any HLA allele and breast cancer risk at P
METHOD: The prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance.
RESULTS: Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0.902 for patients with ER-positive tumours (p = 2.3 × 10-6) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted.
CONCLUSION: The inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predictions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration.
METHODS: Participants enrolled in a regional Asian HIV-infected cohort with weight and height measurements at ART initiation were eligible for inclusion in the analysis. Factors associated with weight changes and incident MetS (according to the International Diabetic Federation (IDF) definition) were analysed using linear mixed models and Cox regression, respectively. Competing-risk regression models were used to investigate the association of MetS with all-cause mortality.
RESULTS: Among 4931 people living with HIV (PLWH), 66% were male. At ART initiation, the median age was 34 [interquartile range (IQR) 29-41] years, and the median (IQR) weight and body mass index (BMI) were 55 (48-63) kg and 20.5 (18.4-22.9) kg/m2 , respectively. At 1, 2 and 3 years of ART, overall mean (± standard deviation) weight gain was 2.2 (±5.3), 3.0 (±6.2) and 3.7 (±6.5) kg, respectively. Participants with baseline CD4 count ≤ 200 cells/µL [weight difference (diff) = 2.2 kg; 95% confidence interval (CI) 1.9-2.5 kg] and baseline HIV RNA ≥ 100 000 HIV-1 RNA copies/mL (diff = 0.6 kg; 95% CI 0.2-1.0 kg), and those starting with integrase strand transfer inhibitor (INSTI)-based ART (diff = 2.1 kg; 95% CI 0.7-3.5 kg vs. nonnucleoside reverse transcriptase inhibitors) had greater weight gain. After exclusion of those with abnormal baseline levels of MetS components, 295/3503 had incident MetS [1.18 (95% CI 1.05-1.32)/100 person-years (PY)]. The mortality rate was 0.7 (95% CI 0.6-0.8)/100 PY. MetS was not significantly associated with all-cause mortality in the adjusted model (P = 0.236).
CONCLUSIONS: Weight gain after ART initiation was significantly higher among those initiating ART with lower CD4 count, higher HIV RNA and an INSTI-based regimen after controlling for baseline BMI. Greater efforts to identify and manage MetS among PLWH are needed.
METHODS: The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases).
RESULTS: The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk.
CONCLUSION: PRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry.
METHODS: A descriptive, cross-sectional, online study, conducted between October-November 2020, assessed the impact of COVID-19 on HIV prevention and care among people living with HIV (PLHIV), key populations (KPs), and healthcare providers (HCPs). The study populations were recruited across ten Asian countries/territories, covering Hong Kong, India, Japan, Malaysia, Philippines, Singapore, Korea, Taiwan, Thailand, and Vietnam.
RESULTS: Across the region, 702 PLHIV, 551 KPs, and 145 HCPs were recruited. Both PLHIV and KPs reported decreased or had yet to visit hospitals/clinics (PLHIV: 35.9%; KPs: 57.5%), reduced HIV RNA viral load testing (21.9%; 47.3%), and interruptions in antiretroviral therapy (ART) (22.3%) or decreased/complete stop of HIV prevention medication consumption (40.9%). Travel constraints (40.6%), financial issues (28.9%), and not receiving prescription refills (26.9%) were common reasons for interrupted ART access, whereas reduced engagements in behaviours that could increase the risks of HIV acquisition and transmission (57.7%), travel constraints (41.8%), and less hospital/clinic visits (36.7%) underlie the disruptions in HIV preventive medications. Decreased visits from PLHIV/KPs and rescheduled appointments due to clinic closure were respectively reported by 50.7%-52.1% and 15.6%-17.0% of HCPs; 43.6%-61.9% observed decreased ART/preventive medication refills. Although 85.0% of HCPs adopted telemedicine to deliver HIV care services, 56.4%-64.1% of PLHIV/KPs were not using telehealth services.
CONCLUSIONS: The COVID-19 pandemic substantially disrupted HIV prevention to care continuum in Asia at the time of the study. The findings highlighted differences in HIV prevention to care continuum via telehealth services utilisation by PLHIV, KPs, and HCPs. Efforts are needed to optimise infrastructure and adapt systems for continued HIV care with minimal disruptions during health emergency crises.
METHODS: We investigated HIV treatment outcomes among people who acquired HIV via injecting drug use in the TREAT Asia HIV Observational Database (TAHOD) between January 2003 and March 2019. Trends in CD4 count and viral suppression (VS, HIV viral load <1000 copies/mL) were assessed. Factors associated with mean CD4 changes were analysed using repeated measures linear regression, and combined AIDS event and mortality were analysed using survival analysis.
RESULTS: Of 622 PWID from 12 countries in the Asia-Pacific, 93% were male and the median age at ART initiation was 31 years (IQR, 28 to 34). The median pre-ART CD4 count was 71 cells/µL. CD4 counts increased over time, with a mean difference of 401 (95% CI, 372 to 457) cells/µL at year-10 (n = 78). Higher follow-up HIV viral load and pre-ART CD4 counts were associated with smaller increases in CD4 counts. Among 361 PWID with ≥1 viral load after six months on ART, proportions with VS were 82%, 88% and 93% at 2-, 5- and 10-years following ART initiation. There were 52 new AIDS-defining events and 50 deaths during 3347 person-years of follow-up (PYS) (incidence 3.05/100 PYS, 95% CI, 2.51 to 3.70). Previous AIDS or TB diagnosis, lower current CD4 count and adherence <95% were associated with combined new AIDS-defining event and death.
CONCLUSIONS: Despite improved outcomes over time, our findings highlight the need for rapid ART initiation and adherence support among PWID within Asian settings.
METHODS: Participants who were enrolled between January 2003 and March 2019 in a regional Asia HIV cohort with weight and height measurements prior to antiretroviral therapy (ART) initiation were included. Factors associated with mean CD4 increase were analysed using repeated-measures linear regression. Time to first VF after 6 months on ART and time to first development of CVD risk markers were analysed using Cox regression models. Sensitivity analyses were done adjusting for Asian BMI thresholds.
RESULTS: Of 4993 PLHIV (66% male), 62% had pre-treatment BMI in the normal range (18.5-25.0 kg/m2 ), while 26%, 10% and 2% were underweight ( 30 kg/m2 ), respectively. Both higher baseline and time-updated BMI were associated with larger CD4 gains compared with normal BMI. After adjusting for Asian BMI thresholds, higher baseline BMIs of 23-27.5 and > 27.5 kg/m2 were associated with larger CD4 increases of 15.6 cells/µL [95% confidence interval (CI): 2.9-28.3] and 28.8 cells/µL (95% CI: 6.6-50.9), respectively, compared with normal BMI (18.5-23 kg/m2 ). PLHIV with BMIs of 25-30 and > 30 kg/m2 were 1.27 times (95% CI: 1.10-1.47) and 1.61 times (95% CI: 1.13-2.24) more likely to develop CVD risk factors. No relationship between pre-treatment BMI and VF was observed.
CONCLUSIONS: High pre-treatment BMI was associated with better immune reconstitution and CVD risk factor development in an Asian PLHIV cohort.
METHODS: We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer-specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype.
RESULTS: There was no evidence of heterogeneous associations between risk factors and mortality by subtype (P adj > 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5-25 kg/m2 [HR (95% confidence interval (CI), 1.19 (1.06-1.34)]; current versus never smoking [1.37 (1.27-1.47)], high versus low physical activity [0.43 (0.21-0.86)], age ≥30 years versus <20 years at first pregnancy [0.79 (0.72-0.86)]; >0-<5 years versus ≥10 years since last full-term birth [1.31 (1.11-1.55)]; ever versus never use of oral contraceptives [0.91 (0.87-0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen-progestin therapy [0.61 (0.54-0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02-1.21) for current versus never smoking.
CONCLUSIONS: We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype.
IMPACT: Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.
METHODS: Adults > 18 years of age on second-line ART for ≥ 6 months were eligible. Cross-sectional data on HIV viral load (VL) and genotypic resistance testing were collected or testing was conducted between July 2015 and May 2017 at 12 Asia-Pacific sites. Virological failure (VF) was defined as VL > 1000 copies/mL with a second VL > 1000 copies/mL within 3-6 months. FASTA files were submitted to Stanford University HIV Drug Resistance Database and RAMs were compared against the IAS-USA 2019 mutations list. VF risk factors were analysed using logistic regression.
RESULTS: Of 1378 patients, 74% were male and 70% acquired HIV through heterosexual exposure. At second-line switch, median [interquartile range (IQR)] age was 37 (32-42) years and median (IQR) CD4 count was 103 (43.5-229.5) cells/µL; 93% received regimens with boosted protease inhibitors (PIs). Median duration on second line was 3 years. Among 101 patients (7%) with VF, CD4 count > 200 cells/µL at switch [odds ratio (OR) = 0.36, 95% confidence interval (CI): 0.17-0.77 vs. CD4 ≤ 50) and HIV exposure through male-male sex (OR = 0.32, 95% CI: 0.17-0.64 vs. heterosexual) or injecting drug use (OR = 0.24, 95% CI: 0.12-0.49) were associated with reduced VF. Of 41 (41%) patients with resistance data, 80% had at least one RAM to nonnucleoside reverse transcriptase inhibitors (NNRTIs), 63% to NRTIs, and 35% to PIs. Of those with PI RAMs, 71% had two or more.
CONCLUSIONS: There were low proportions with VF and significant RAMs in our cohort, reflecting the durability of current second-line regimens.