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  • 1
    Keywords: BLOOD ; MODEL ; DISEASE ; RISK ; PATIENT ; ARTHRITIS ; RISK-FACTORS ; T cell ; T-CELL ; TYPE-1 ; ASSOCIATION ; DISORDER ; LYMPHOMA ; risk factors ; SWEDEN ; diabetes ; case-control studies ; CLUES ; MULTIPLE-SCLEROSIS ; FOLLICULAR LYMPHOMA ; INFLAMMATORY-BOWEL-DISEASE ; SYSTEMIC-LUPUS-ERYTHEMATOSUS ; DISORDERS ; case-control study ; MEDICAL HISTORY ; POPULATION-BASED COHORT ; PATTERN ; T-CELL LYMPHOMA ; rheumatoid arthritis ; RHEUMATOID-ARTHRITIS ; non-Hodgkin lymphoma ; analysis ; SUBTYPES ; CELIAC-DISEASE ; PARTICIPANTS ; multiple sclerosis ; pooled analysis ; USA ; CANCER INCIDENCE ; RISK-FACTOR ; B-CELL ; ANEMIA ; PERNICIOUS-ANEMIA ; systemic ; RATIO ; non Hodgkin lymphoma ; POOLED-ANALYSIS ; non-Hodgkin ; CONSORTIUM ; CONFIDENCE-INTERVALS ; MARGINAL ZONE LYMPHOMAS ; INTERLYMPH ; AUTOIMMUNE ; HEMATOPOIETIC CANCER ; hemolytic anemia ; PRIMARY SJOGRENS-SYNDROME ; systemic lupus erythematosus
    Abstract: Some autoimmune disorders are increasingly recognized as risk factors for non-Hodgkin lymphoma (NHL) overall, but large-scale systematic assessments of risk of NHL subtypes are lacking. We performed a pooled analysis of self-reported autoimmune conditions and risk of NHL and subtypes, including 29 423 participants in 12 case-control studies. We computed pooled odds ratios (OR) and 95% confidence intervals (CI) in a joint fixed-effects model. Sjogren syndrome was associated with a 6.5-fold increased risk of NHL, a 1000-fold increased risk of parotid gland marginal zone lymphoma (OR = 996; 95% CI, 216-4596), and with diffuse large B-cell and follicular lymphomas. Systemic lupus erythematosus was associated with a 2.7-fold increased risk of NHL and with diffuse large B-cell and marginal zone lymphomas. Hemolytic anemia was associated with diffuse large B-cell NHL. T-cell NHL risk was increased for patients with celiac disease and psoriasis. Results for rheumatoid arthritis were heterogeneous between studies. Inflammatory bowel disorders, type 1 diabetes, sarcoidosis, pernicious anemia, and multiple sclerosis were not associated with risk of NHL or subtypes. Thus, specific autoimmune disorders are associated with NHL risk beyond the development of rare NHL subtypes in affected organs. The pattern of associations with NHL subtypes may harbor clues to lymphomagenesis
    Type of Publication: Journal article published
    PubMed ID: 18263783
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  • 2
    Publication Date: 2018-04-12
    Description: Objectives To investigate between-hospital variation in the probability of reoperation within 90 days of initial breast-conserving surgery (BCS), and the contribution of health system-level and other factors. Design Population-based, retrospective cohort study. Setting New South Wales (NSW), Australia. Participants Linked administrative hospitalisation data were used to define a cohort of adult women undergoing initial BCS for breast cancer in NSW between 1 July 2002 and 31 December 2013. Primary outcome measures Multilevel, cross-classified models with patients clustered within hospitals and residential areas were used to examine factors associated with any reoperation, and either re-excision or mastectomy, within 90 days. Results Of 34 458 women undergoing BCS, 29.1% underwent reoperation within 90 days, half of which were mastectomies. Overall, the probability of reoperation decreased slightly over time. However, there were divergent patterns by reoperation type; the probability of re-excision increased alongside a concomitant decrease in the probability of mastectomy. Significant between-hospital variation was observed. Non-metropolitan location and surgery at low-volume hospitals were associated with a higher overall probability of reoperation, and of mastectomy specifically, after accounting for patient-level factors, calendar year and area-level socioeconomic status. The magnitude of association with geographical location and surgical volume decreased over time. Conclusions Reoperation rates within 90 days of BCS varied significantly between hospitals. For women undergoing mastectomy after BCS, this represents a dramatic change in clinical course. Multilevel modelling suggests unwarranted clinical variation may be an issue, likely due to disparities in access to multidisciplinary breast cancer care and preoperative diagnostic procedures. However, the observed reduction in disparities over time is encouraging and indicates that guidelines and policy initiatives have the potential to improve regional breast cancer care.
    Keywords: Open access, Oncology
    Electronic ISSN: 2044-6055
    Topics: Medicine
    Published by BMJ Publishing
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  • 3
    Publication Date: 2018-02-28
    Description: Objective This observational study critically explored the performance of different predictive risk models simulating three data access scenarios, comparing: (1) sociodemographic and clinical profiles; (2) consistency in high-risk designation across models; and (3) persistence of high-risk status over time. Methods Cross-sectional health survey data (2006–2009) for more than 260 000 Australian adults 45+ years were linked to longitudinal individual hospital, primary care, pharmacy and mortality data. Three risk models predicting acute emergency hospitalisations were explored, simulating conditions where data are accessed through primary care practice management systems, or through hospital-based electronic records, or through a hypothetical ‘full’ model using a wider array of linked data. High-risk patients were identified using different risk score thresholds. Models were reapplied monthly for 24 months to assess persistence in high-risk categorisation. Results The three models displayed similar statistical performance. Three-quarters of patients in the high-risk quintile from the ‘full’ model were also identified using the primary care or hospital-based models, with the remaining patients differing according to age, frailty, multimorbidity, self-rated health, polypharmacy, prior hospitalisations and imminent mortality. The use of higher risk prediction thresholds resulted in lower levels of agreement in high-risk designation across models and greater morbidity and mortality in identified patient populations. Persistence of high-risk status varied across approaches according to updated information on utilisation history, with up to 25% of patients reassessed as lower risk within 1 year. Conclusion/implications Small differences in risk predictors or risk thresholds resulted in comparatively large differences in who was classified as high risk and for how long. Pragmatic predictive risk modelling design decisions based on data availability or projected high-risk patient numbers may therefore influence individuals identified as high-risk, overall case mix and risk persistence. Routine data linkage would enable greater flexibility in developing and optimising predictive risk models appropriate to both case-finding and performance measurement applications.
    Keywords: Health informatics, Health policy, Open access, Health informatics, Health economics
    Electronic ISSN: 2044-6055
    Topics: Medicine
    Published by BMJ Publishing
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