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: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium.
RESULTS: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10(-4); OR, 1.04; 95% confidence interval (CI), 1.02-1.07] and rs77928427 (P = 1.86 × 10(-4); OR, 1.04; 95% CI, 1.02-1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r(2) ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor-binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue.
CONCLUSION: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2.
IMPACT: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk.
SETTINGS: A validation study among people living with HIV(PLHIV) aged ≥18 years among the cohorts in the Asia-Pacific region.
METHODS: PLHIV with baseline eGFR>60 mL/min/1.73m were included for validation of the D:A:D CKD full version and the short version without cardiovascular risk factors. Those with <3 eGFR measurements from baseline or previous exposure to potentially nephrotoxic antiretrovirals were excluded. Kaplan-Meier methods were used to estimate the probability of CKD development. Area Under the Receiver Operating Characteristics (AUROC) was also used to validate the risk score.
RESULTS: We included 5,701 participants in full model(median 8.1 [IQR 4.8-10.9] years follow-up) and 9,791 in short model validation(median 4.9 [IQR 2.5-7.3] years follow-up). The crude incidence rate of CKD was 8.1 (95%CI 7.3-8.9) per 1,000 person-years(PYS) in the full model cohort and 10.5 (95%CI 9.6-11.4) per 1,000 PYS in the short model cohort. The progression rates for CKD at 10 years in the full model cohort were 2.7%, 8.9% and 26.1% for low-, medium- and high-risk groups, and 3.5%, 11.7% and 32.4% in the short model cohort. The AUROC for the full and short risk score was 0.81 (95%CI 0.79-0.83) and 0.83 (95%CI 0.81-0.85), respectively.
CONCLUSION: The D:A:D CKD full- and short-risk score performed well in predicting CKD events among Asian PLHIV. These risk prediction models may be useful to assist clinicians in identifying individuals at high risk of developing CKD.
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 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 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: PLHIV from a regional observational cohort without DM prior to antiretroviral therapy (ART) initiation were included in the analysis. DM was defined as having a fasting blood glucose ≥126 mg/dL, glycated haemoglobin ≥6.5%, a two-hour plasma glucose ≥200 mg/dL, or a random plasma glucose ≥200 mg/dL. A Cox regression model, stratified by site, was used to identify risk factors associated with DM.
RESULTS AND DISCUSSION: Of the 1927 participants included, 127 were diagnosed with DM after ART initiation. Median follow-up time from ART initiation to DM diagnosis was 5.9 years (interquartile range (IQR): 2.8 to 8.9 years). The crude incidence rate of DM was 1.08 per 100 person-years (100 PYS), 95% confidence interval (CI) (0.9 to 1.3). In the multivariate analysis, later years of follow-up (2011 to 2013: HR = 2.34, 95% CI 1.14 to 4.79, p = 0.02; and 2014 to 2017: HR = 7.20, 95% CI 3.27 to 15.87, p 50 years: HR = 4.19, 95% CI 2.12 to 8.28, p 30 kg/m2 (HR = 4.3, 95% CI 1.53 to 12.09, p = 0.006) compared to BMI <18.5 kg/m2 , and high blood pressure (HR = 2.05, 95% CI 1.16 to 3.63, p = 0.013) compared to those without high blood pressure, were associated with developing DM. The hazard was reduced for females (HR = 0.47, 95% CI 0.28 to 0.80, p = 0.006).
CONCLUSIONS: Type 2 DM in HIV-infected Asians was associated with later years of follow-up, high blood pressure, obesity and older age. This highlights the importance of monitoring and routine screening for non-communicable diseases including DM as PLHIV age.
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: 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
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: Incidence of malignancy after cohort enrollment was evaluated. Factors associated with development of hematological and nonhematological malignancy were analyzed using competing risk regression and survival time using Kaplan-Meier.
RESULTS: Of 7455 patients, 107 patients (1%) developed a malignancy: 34 (0.5%) hematological [0.08 per 100 person-years (/100PY)] and 73 (1%) nonhematological (0.17/100PY). Of the hematological malignancies, non-Hodgkin lymphoma was predominant (n = 26, 76%): immunoblastic (n = 6, 18%), Burkitt (n = 5, 15%), diffuse large B-cell (n = 5, 15%), and unspecified (n = 10, 30%). Others include central nervous system lymphoma (n = 7, 21%) and myelodysplastic syndrome (n = 1, 3%). Nonhematological malignancies were mostly Kaposi sarcoma (n = 12, 16%) and cervical cancer (n = 10, 14%). Risk factors for hematological malignancy included age >50 vs. ≤30 years [subhazard ratio (SHR) = 6.48, 95% confidence interval (CI): 1.79 to 23.43] and being from a high-income vs. a lower-middle-income country (SHR = 3.97, 95% CI: 1.45 to 10.84). Risk was reduced with CD4 351-500 cells/µL (SHR = 0.20, 95% CI: 0.05 to 0.74) and CD4 >500 cells/µL (SHR = 0.14, 95% CI: 0.04 to 0.78), compared to CD4 ≤200 cells/µL. Similar risk factors were seen for nonhematological malignancy, with prior AIDS diagnosis showing a weak association. Patients diagnosed with a hematological malignancy had shorter survival time compared to patients diagnosed with a nonhematological malignancy.
CONCLUSIONS: Nonhematological malignancies were common but non-Hodgkin lymphoma was more predominant in our cohort. PLHIV from high-income countries were more likely to be diagnosed, indicating a potential underdiagnosis of cancer in low-income settings.