METHODS: Patients (age >18 years) who met the criteria for systemic lupus erythematosus were recruited from 13 centres in Australia, Indonesia, Japan, Malaysia, the Philippines, Singapore, Taiwan, and Thailand, and followed longitudinally. Disease activity (Systemic Lupus Erythematosus Disease Activity Index 2000 [SLEDAI-2K] and Physician Global Assessment [PGA] scores) and treatment details were recorded at each visit (at least once every 6 months), and organ damage measured annually according to the Systemic Lupus International Collaborating Clinics Damage Index (SDI). Glucocorticoid use during the study period was recorded as any exposure to prednisolone, cumulative prednisolone exposure, and time-adjusted mean daily prednisolone dose. Multivariate survival analyses were used to examine time-dependent associations of glucocorticoid use with damage accrual (defined as an increase of ≥1 on SDI). A SLEDAI-2K score of 0 was taken to indicate the absence of clinical and serological disease activity; a subset of patients without disease activity during the study were defined by a time-adjusted mean SLEDAI-2K (AMS) score of 0.
FINDINGS: Between May 1, 2013, and Dec 31, 2016, 1707 patients were recruited. Over a median observation period of 2·2 years (IQR 1·5-3·0), damage accrual events were observed in 255 (14·9%) patients. 1405 (82·3%) of patients were exposed to prednisolone, with a median time-adjusted mean prednisolone dose of 5·0 mg/day (IQR 1·9-8·8). As SLEDAI-2K and PGA scores were highly correlated, two multivariable models were set, each including one of these two variables. In the model including AMS score, baseline SDI damage (SDI >0) was independently associated with damage accrual (HR 1·32 [95% CI 1·01-1·73], p=0·0427). In the other model, time-adjusted mean PGA score was independently associated with damage accrual (1·05 [1·02-1·08], p=0·0012). In both models, factors independently associated with damage accrual included time-adjusted mean prednisolone dose, age at enrolment, and ethnicity (Asian vs non-Asians). 157 (9·2%) patients had an AMS score of 0 (no disease activity), among whom 103 (65·6%) had glucocorticoid exposure and the median time-adjusted mean prednisolone dose was 2·0 mg/day (IQR 0·0-5·0). Accrual of irreversible organ damage occurred in 21 (13·4%) of these patients and was independently associated with time-adjusted mean prednisolone dose (HR 1·14 [95% CI 1·03-1·26], p=0·0117), time-adjusted mean PGA score (1·13 [1·03-1·23], p=0·0144), and age at enrolment (1·04 [1·01-1·07], p=0·0061), but not baseline SDI damage (0·94 [0·43-2·06], p=0·8675).
INTERPRETATION: Glucocorticoid use contributes to damage accrual in systemic lupus erythematosus independently of the presence of clinical or serological disease activity.
FUNDING: UCB Pharma, GlaxoSmithKline, Janssen, Bristol-Myers Squibb, and AstraZeneca (to the Asia-Pacific Lupus Collaboration).
METHODS: In a regional HIV observational cohort in the Asia-Pacific region, patients with viral suppression (2 consecutive viral loads <400 copies/mL) and a CD4 count ≥200 cells per microliter who had CD4 testing 6 monthly were analyzed. Main study end points were occurrence of 1 CD4 count <200 cells per microliter (single CD4 <200) and 2 CD4 counts <200 cells per microliter within a 6-month period (confirmed CD4 <200). A comparison of time with single and confirmed CD4 <200 with biannual or annual CD4 assessment was performed by generating a hypothetical group comprising the same patients with annual CD4 testing by removing every second CD4 count.
RESULTS: Among 1538 patients, the rate of single CD4 <200 was 3.45/100 patient-years and of confirmed CD4 <200 was 0.77/100 patient-years. During 5 years of viral suppression, patients with baseline CD4 200-249 cells per microliter were significantly more likely to experience confirmed CD4 <200 compared with patients with higher baseline CD4 [hazard ratio, 55.47 (95% confidence interval: 7.36 to 418.20), P < 0.001 versus baseline CD4 ≥500 cells/μL]. Cumulative probabilities of confirmed CD4 <200 was also higher in patients with baseline CD4 200-249 cells per microliter compared with patients with higher baseline CD4. There was no significant difference in time to confirmed CD4 <200 between biannual and annual CD4 measurement (P = 0.336).
CONCLUSIONS: Annual CD4 monitoring in virally suppressed HIV patients with a baseline CD4 ≥250 cells per microliter may be sufficient for clinical management.
METHODS: Patients initiating cART between 2006 and 2013 were included. TI was defined as stopping cART for >1 day. Treatment failure was defined as confirmed virological, immunological or clinical failure. Time to treatment failure during cART was analysed using Cox regression, not including periods off treatment. Covariables with P < 0.10 in univariable analyses were included in multivariable analyses, where P < 0.05 was considered statistically significant.
RESULTS: Of 4549 patients from 13 countries in Asia, 3176 (69.8%) were male and the median age was 34 years. A total of 111 (2.4%) had TIs due to AEs and 135 (3.0%) had TIs for other reasons. Median interruption times were 22 days for AE and 148 days for non-AE TIs. In multivariable analyses, interruptions >30 days were associated with failure (31-180 days HR = 2.66, 95%CI (1.70-4.16); 181-365 days HR = 6.22, 95%CI (3.26-11.86); and >365 days HR = 9.10, 95% CI (4.27-19.38), all P < 0.001, compared to 0-14 days). Reasons for previous TI were not statistically significant (P = 0.158).
CONCLUSIONS: Duration of interruptions of more than 30 days was the key factor associated with large increases in subsequent risk of treatment failure. If TI is unavoidable, its duration should be minimised to reduce the risk of failure after treatment resumption.
Objective: To examine the effects of a quality improvement intervention comprising information and communications technology and contact with nonphysician personnel on the care and cardiometabolic risk factors of patients with type 2 diabetes in 8 Asia-Pacific countries.
Design, Setting, and Participants: This 12-month multinational open-label randomized clinical trial was conducted from June 28, 2012, to April 28, 2016, at 50 primary care or hospital-based diabetes centers in 8 Asia-Pacific countries (India, Indonesia, Malaysia, the Philippines, Singapore, Taiwan, Thailand, and Vietnam). Six countries were low and middle income, and 2 countries were high income. The study was conducted in 2 phases; phase 1 enrolled 7537 participants, and phase 2 enrolled 13 297 participants. Participants in both phases were randomized on a 1:1 ratio to intervention or control groups. Data were analyzed by intention to treat and per protocol from July 3, 2019, to July 21, 2020.
Interventions: In both phases, the intervention group received 3 care components: a nurse-led Joint Asia Diabetes Evaluation (JADE) technology-guided structured evaluation, automated personalized reports to encourage patient empowerment, and 2 or more telephone or face-to-face contacts by nurses to increase patient engagement. In phase 1, the control group received the JADE technology-guided structured evaluation and automated personalized reports. In phase 2, the control group received the JADE technology-guided structured evaluation only.
Main Outcomes and Measures: The primary outcome was the incidence of a composite of diabetes-associated end points, including cardiovascular disease, chronic kidney disease, visual impairment or eye surgery, lower extremity amputation or foot ulcers requiring hospitalization, all-site cancers, and death. The secondary outcomes were the attainment of 2 or more primary diabetes-associated targets (glycated hemoglobin A1c <7.0%, blood pressure <130/80 mm Hg, and low-density lipoprotein cholesterol <100 mg/dL) and/or 2 or more key performance indices (reduction in glycated hemoglobin A1c≥0.5%, reduction in systolic blood pressure ≥5 mm Hg, reduction in low-density lipoprotein cholesterol ≥19 mg/dL, and reduction in body weight ≥3.0%).
Results: A total of 20 834 patients with type 2 diabetes were randomized in phases 1 and 2. In phase 1, 7537 participants (mean [SD] age, 60.0 [11.3] years; 3914 men [51.9%]; 4855 patients [64.4%] from low- and middle-income countries) were randomized, with 3732 patients allocated to the intervention group and 3805 patients allocated to the control group. In phase 2, 13 297 participants (mean [SD] age, 54.0 [11.1] years; 7754 men [58.3%]; 13 297 patients [100%] from low- and middle-income countries) were randomized, with 6645 patients allocated to the intervention group and 6652 patients allocated to the control group. In phase 1, compared with the control group, the intervention group had a similar risk of experiencing any of the primary outcomes (odds ratio [OR], 0.94; 95% CI, 0.74-1.21) but had an increased likelihood of attaining 2 or more primary targets (OR, 1.34; 95% CI, 1.21-1.49) and 2 or more key performance indices (OR, 1.18; 95% CI, 1.04-1.34). In phase 2, the intervention group also had a similar risk of experiencing any of the primary outcomes (OR, 1.02; 95% CI, 0.83-1.25) and had a greater likelihood of attaining 2 or more primary targets (OR, 1.25; 95% CI, 1.14-1.37) and 2 or more key performance indices (OR, 1.50; 95% CI, 1.33-1.68) compared with the control group. For attainment of 2 or more primary targets, larger effects were observed among patients in low- and middle-income countries (OR, 1.50; 95% CI, 1.29-1.74) compared with high-income countries (OR, 1.20; 95% CI, 1.03-1.39) (P = .04).
Conclusions and Relevance: In this 12-month clinical trial, the use of information and communications technology and nurses to empower and engage patients did not change the number of clinical events but did reduce cardiometabolic risk factors among patients with type 2 diabetes, especially those in low- and middle-income countries in the Asia-Pacific region.
Trial Registration: ClinicalTrials.gov Identifier: NCT01631084.
PURPOSE: Minimum clinical standards for assessment and management of osteoporosis are needed in the Asia-Pacific (AP) region to inform clinical practice guidelines (CPGs) and to improve osteoporosis care. We present the framework of these clinical standards and describe its development.
METHODS: We conducted a structured comparative analysis of existing CPGs in the AP region using a "5IQ" model (identification, investigation, information, intervention, integration, and quality). One-hundred data elements were extracted from each guideline. We then employed a four-round Delphi consensus process to structure the framework, identify key components of guidance, and develop clinical care standards.
RESULTS: Eighteen guidelines were included. The 5IQ analysis demonstrated marked heterogeneity, notably in guidance on risk factors, the use of biochemical markers, self-care information for patients, indications for osteoporosis treatment, use of fracture risk assessment tools, and protocols for monitoring treatment. There was minimal guidance on long-term management plans or on strategies and systems for clinical quality improvement. Twenty-nine APCO members participated in the Delphi process, resulting in consensus on 16 clinical standards, with levels of attainment defined for those on identification and investigation of fragility fractures, vertebral fracture assessment, and inclusion of quality metrics in guidelines.
CONCLUSION: The 5IQ analysis confirmed previous anecdotal observations of marked heterogeneity of osteoporosis clinical guidelines in the AP region. The Framework provides practical, clear, and feasible recommendations for osteoporosis care and can be adapted for use in other such vastly diverse regions. Implementation of the standards is expected to significantly lessen the global burden of osteoporosis.
METHODS: HIV-infected adults enrolled in the TREAT Asia HIV Observational Database were eligible if they had an HIV RNA measurement documented at the time of ART initiation. The dataset was randomly split into a derivation data set (75% of patients) and a validation data set (25%). Factors associated with pre-treatment HIV RNA <100,000 copies/mL were evaluated by logistic regression adjusted for study site. A prediction model and prediction scores were created.
RESULTS: A total of 2592 patients were enrolled for the analysis. Median [interquartile range (IQR)] age was 35.8 (29.9-42.5) years; CD4 count was 147 (50-248) cells/mm3; and pre-treatment HIV RNA was 100,000 (34,045-301,075) copies/mL. Factors associated with pre-treatment HIV RNA <100,000 copies/mL were age <30 years [OR 1.40 vs. 41-50 years; 95% confidence interval (CI) 1.10-1.80, p = 0.01], body mass index >30 kg/m2(OR 2.4 vs. <18.5 kg/m2; 95% CI 1.1-5.1, p = 0.02), anemia (OR 1.70; 95% CI 1.40-2.10, p 350 cells/mm3(OR 3.9 vs. <100 cells/mm3; 95% CI 2.0-4.1, p 2000 cells/mm3(OR 1.7 vs. <1000 cells/mm3; 95% CI 1.3-2.3, p 25 yielded the sensitivity of 46.7%, specificity of 79.1%, positive predictive value of 67.7%, and negative predictive value of 61.2% for prediction of pre-treatment HIV RNA <100,000 copies/mL among derivation patients.
CONCLUSION: A model prediction for pre-treatment HIV RNA <100,000 copies/mL produced an area under the ROC curve of 0.70. A larger sample size for prediction model development as well as for model validation is warranted.