METHODS: Demographics, diagnosis, comorbidities, disease activity, treatments and PROMIS instrument data were analysed. Primary outcomes were PROMIS Global Physical Health (GPH) and Global Mental Health (GMH) scores. Factors affecting GPH and GMH scores in IIMs were identified using multivariable regression analysis.
RESULTS: We analysed responses from 1582 IIM, 4700 non-IIM AIRD and 545 nrAID patients and 3675 controls gathered through 23 May 2022. The median GPH scores were the lowest in IIM and non-IIM AIRD patients {13 [interquartile range (IQR) 10-15] IIMs vs 13 [11-15] non-IIM AIRDs vs 15 [13-17] nrAIDs vs 17 [15-18] controls, P
METHODS: The first and second COVAD patient self-reported e-surveys were circulated from March to December 2021, and February to June 2022 (ongoing). We collected data on demographics, comorbidities, COVID-19 infection and vaccination history, reasons for hesitancy, and patient reported outcomes. Predictors of hesitancy were analysed using regression models in different groups.
RESULTS: We analysed data from 18 882 (COVAD-1) and 7666 (COVAD-2) respondents. Reassuringly, hesitancy decreased from 2021 (16.5%) to 2022 (5.1%) (OR: 0.26; 95% CI: 0.24, 0.30, P
METHODS: The COVAD-1 and -2 global surveys were circulated in early 2021 and 2022, respectively, and we captured demographics, comorbidities, AIRDs details, COVID-19 infection history and vaccination details. Flares of IIMs were defined as (a) patient self-reported, (b) immunosuppression (IS) denoted, (c) clinical sign directed and (d) with >7.9-point minimal clinically significant improvement difference worsening of Patient-Reported Outcomes Measurement Information System (PROMIS) PROMISPF10a score. Risk factors of flares were analysed using regression models.
RESULTS: Of 15 165 total respondents, 1278 IIMs (age 63 years, 70.3% female, 80.8% Caucasians) and 3453 AIRDs were included. Flares of IIM were seen in 9.6%, 12.7%, 8.7% and 19.6% patients by definitions (a) to (d), respectively, with a median time to flare of 71.5 (10.7-235) days, similar to AIRDs. Patients with active IIMs pre-vaccination (OR 1.2; 95% CI 1.03, 1.6, P = 0.025) were prone to flares, while those receiving rituximab (OR 0.3; 95% CI 0.1, 0.7, P = 0.010) and AZA (OR 0.3, 95% CI 0.1, 0.8, P = 0.016) were at lower risk. Female gender and comorbidities predisposed to flares requiring changes in IS. Asthma (OR 1.62; 95% CI 1.05, 2.50, P = 0.028) and higher pain visual analogue score (OR 1.19; 95% CI 1.11, 1.27, P
METHODS: Retrospective data from 57 centers in patients with stage III NSCLC diagnosed between January 2013 and December 2017 were analyzed. Median progression free survival (mPFS) and median overall survival (mOS) estimates with two sided 95% confidence interval (CI) were determined by applying the Kaplan-Meier survival analysis.
RESULTS: Of the total 1874 patients (median age: 63.0 years [24 to 92]) enrolled in the Asia subset, 74.8% were men, 54.7% had stage IIIA disease, 55.7% had adenocarcinoma, 34.3% had epidermal growth factor receptor mutations (EGFRm) and 50.3% had programmed death-ligand 1 (PD-L1) expression (i.e. PD-L1 ≥1%). Of the 31 treatment approaches as initial therapy, concurrent chemoradiotherapy (CRT) was the most frequent (29.3%), followed by chemotherapy (14.8%), sequential CRT (9.5%), and radiotherapy (8.5%). Targeted therapy alone was used in 81 patients of the overall population. For the Asia cohort, the mPFS and mOS were 12.8 months (95% CI, 12.2-13.7) and 42.3 months (95% CI, 38.1-46.8), respectively. Stage IIIA disease, Eastern Cooperative Oncology Group ≤1, age ≤65 years, adenocarcinoma histology and surgery/concurrent CRT as initial therapy correlated with better mOS (p < 0.05).
CONCLUSIONS: The results demonstrate diverse treatment patterns and survival outcomes in the Asian region. The high prevalence of EGFRm and PD-L1 expression in stage III NSCLC in Asia suggests the need for expanding access to molecular testing for guiding treatment strategies with tyrosine kinase inhibitors and immunotherapies in this region.
METHODS: Prospectively collected longitudinal data from patients in Thailand, Hong Kong, Malaysia, Japan, Taiwan, and South Korea were provided for analysis. Covariates included demographics, hepatitis B and C coinfections, baseline CD4 T lymphocyte count, and plasma HIV-1 RNA levels. Clinical deterioration (a new diagnosis of Centers for Disease Control and Prevention category B/AIDS-defining illness or death) was assessed by proportional hazards models. Surrogate endpoints were 12-month change in CD4 cell count and virologic suppression post therapy, evaluated by linear and logistic regression, respectively.
RESULTS: Of 1105 patients, 1036 (93.8%) infected with CRF01_AE or subtype B were eligible for inclusion in clinical deterioration analyses and contributed 1546.7 person-years of follow-up (median: 413 days, interquartile range: 169-672 days). Patients >40 years demonstrated smaller immunological increases (P = 0.002) and higher risk of clinical deterioration (hazard ratio = 2.17; P = 0.008). Patients with baseline CD4 cell counts >200 cells per microliter had lower risk of clinical deterioration (hazard ratio = 0.373; P = 0.003). A total of 532 patients (48.1% of eligible) had CD4 counts available at baseline and 12 months post therapy for inclusion in immunolgic analyses. Patients infected with subtype B had larger increases in CD4 counts at 12 months (P = 0.024). A total of 530 patients (48.0% of eligible) were included in virological analyses with no differences in response found between genotypes.
CONCLUSIONS: Results suggest that patients infected with CRF01_AE have reduced immunologic response to therapy at 12 months, compared with subtype B-infected counterparts. Clinical deterioration was associated with low baseline CD4 counts and older age. The lack of differences in virologic outcomes suggests that all patients have opportunities for virological suppression.
METHODS: We used the 2003-2013 Taiwanese National Health Insurance Research Database to identify RA patients who started any RA-related medical therapy from 2008 to 2012. Those who initiated etanercept or adalimumab therapy during 2008-2012 were selected as the TNFi group and those who never received biologic disease-modifying anti-rheumatic drug therapy were identified as the comparison group after excluding the patients who had a history of TB or human immunodeficiency virus infection/acquired immune deficiency syndrome. We used propensity score matching (1:6) for age, sex, and the year of the drug index date to re-select the TNFi group and the non-TNFi controls. After adjusting for potential confounders, hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated to examine the 1-year TB risk in the TNFi group compared with the non-TNFi controls. Subgroup analyses according to the year of treatment initiation and specific TNFi therapy were conducted to assess the trend of 1-year TB risk in TNFi users from 2008 to 2012.
RESULTS: This study identified 5,349 TNFi-treated RA patients and 32,064 matched non-TNFi-treated controls. The 1-year incidence rates of TB were 1,513 per 105 years among the TNFi group and 235 per 105 years among the non-TNFi controls (incidence rate ratio, 6.44; 95% CI, 4.69-8.33). After adjusting for age, gender, disease duration, comoridities, history of TB, and concomitant medications, TNFi users had an increased 1-year TB risk (HR, 7.19; 95% CI, 4.18-12.34) compared with the non-TNFi-treated controls. The 1-year TB risk in TNFi users increased from 2008 to 2011 and deceased in 2012 when the Food and Drug Administration in Taiwan announced the Risk Management Plan for patients scheduled to receive TNFi therapy.
CONCLUSION: This study showed that the 1-year TB risk in RA patients starting TNFi therapy was significantly higher than that in non-TNFi controls in Taiwan from 2008 to 2012.
METHODS: This study enrolled 147 SLE patients from the Asia Pacific Lupus Collaboration (APLC) cohort, who had BMD and TBS assessed from January 2018 until December 2018. Twenty-eight patients sustaining VF and risk factors associated with increased fracture occurrence were evaluated. Independent risk factors and diagnostic accuracy of VF were analyzed by logistic regression and ROC curve, respectively.
RESULT: The prevalence of vertebral fracture among SLE patients was 19%. BMD, T-score, TBS, and TBS T-score were significantly lower in the vertebral fracture group. TBS exhibited higher positive predictive value and negative predictive value than L spine and left femur BMD for vertebral fractures. Moreover, TBS had a higher diagnostic accuracy than densitometric measurements (area under curve, 0.811 vs. 0.737 and 0.605).
CONCLUSION: Degraded microarchitecture by TBS was associated with prevalent vertebral fractures in SLE patients. Our result suggests that TBS can be a complementary tool for assessing vertebral fracture prevalence in this population.
METHODS: The COVAD surveys were used to extract data on flare demographics, comorbidities, COVID-19 history, and vaccination details for patients with AIRDs. Flares following vaccination were identified as patient-reported (a), increased immunosuppression (b), clinical exacerbations (c) and worsening of PROMIS scores (d). We studied flare characteristics and used regression models to differentiate flares among various AIRDs.
RESULTS: Of 15 165 total responses, the incidence of flares in 3453 patients with AIRDs was 11.3%, 14.8%, 9.5% and 26.7% by definitions a-d, respectively. There was moderate agreement between patient-reported and immunosuppression-defined flares (K = 0.403, P = 0.022). Arthritis (61.6%) and fatigue (58.8%) were the most commonly reported symptoms. Self-reported flares were associated with higher comorbidities (P = 0.013), mental health disorders (MHDs) (P