Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 3 de 3
Filter
Add more filters










Database
Language
Publication year range
1.
Int J Rheum Dis ; 26(8): 1557-1570, 2023 Aug.
Article in English | MEDLINE | ID: mdl-37338061

ABSTRACT

AIM: To explore the association between systemic lupus erythematosus (SLE) with the risk of cancer development and subsequent 5-year mortality in Western Australia (WA). METHODS: Population-level, data linkage study of SLE patients (n = 2111) and general population comparators (n = 21 110) hospitalized between 1980 and 2014. SLE patients (identified by ICD-9-CM: 695.4, 710.0, and ICD-10-AM: L93.0, M32.0) were nearest matched (10:1) for age, sex, Aboriginality, and temporality. Follow up was from time zero (index SLE hospitalization) to cancer development, death or 31 December 2014. We assessed the risk of cancer development and subsequent 5-year mortality between SLE patients and comparators with univariate and multivariate-adjusted Cox proportional hazards regression models. RESULTS: SLE patients had similar multivariate-adjusted risk (adjusted hazard ratio [aHR] 1.03, 95% confidence interval [CI] 0.93-1.15; p = .583) of cancer development. Cancer development risk was higher in SLE patients <40 years old (aHR 1.58, 95% CI 1.29-1.94; p < .001), and from 1980 to 1999 (aHR 1.16, 95% CI 1.02-1.31; p < .001). SLE patients had higher risk of developing cancer of the oropharynx (aHR 2.13, 95% CI 1.30-3.50), vulvo-vagina (aHR 3.22, 95% CI 1.34-7.75), skin (aHR 1.20, 95% CI 1.01-1.43), musculoskeletal tissues (aHR 2.26, 95% CI 1.16-4.40), and hematological tissues (aHR 1.78 95% CI 1.25-2.53), all p < .05. After cancer development, SLE patients had increased risk of 5-year mortality (aHR 1.31, 95% CI 1.06-1.61); highest in patients <50 years old (aHR 2.03, 95% CI 1.03-4.00), and in those with reproductive system and skin cancers. CONCLUSIONS: Hospitalized SLE patients had increased risk of multiple cancer sub-types. Following cancer development, SLE patients had increased risk of 5-year mortality. There is scope to improve cancer prevention and surveillance in SLE patients. TRIAL REGISTRATION: Not applicable. This low-risk risk study used de-identified administrative linked health data.


Subject(s)
Lupus Erythematosus, Systemic , Neoplasms , Female , Humans , Adult , Middle Aged , Risk Factors , Lupus Erythematosus, Systemic/diagnosis , Lupus Erythematosus, Systemic/epidemiology , Proportional Hazards Models , Neoplasms/diagnosis , Neoplasms/epidemiology , Western Australia/epidemiology
2.
Lupus Sci Med ; 8(1)2021 10.
Article in English | MEDLINE | ID: mdl-34667085

ABSTRACT

OBJECTIVE: Mortality rates for patients with SLE have not been reported in Australia. This study determined the association between a hospitalisation for SLE with mortality. METHODS: Population-level cohort study of patients with SLE (n=2112; 25 710 person-years) and general population comparators (controls) (n=21, 120; 280 637 person-years) identified from hospital records contained within the WA Rheumatic Disease Epidemiological Registry from 1980 to 2013. SLE was identified by ICD-9-CM: 695.4, 710.0, ICD-10-AM: L93.0, M32.0. Controls were nearest matched (10:1) for age, sex, Aboriginality and temporality. Using longitudinal linked health data, we assessed the association between a hospitalisation for SLE mortality and mortality with univariate and multivariate Cox proportional hazards and competing risks regression models. RESULTS: At timezero, patients with SLE were similar in age (43.96 years), with higher representation of females (85.1% vs 83.4%, p=0.038), Aboriginal Australians (7.8% vs 6.0%) and smokers (20.5% vs 13.2%). Before study entry, patients with SLE (mean lookback 9 years) had higher comorbidity accrual (Charlson Comorbidity Index ≥1 item (42.0% vs 20.5%)), especially cardiovascular disease (CVD) (44.7% vs 21.0%) and nephritis (16.4% vs 0.5%), all p<0.001. During follow-up (mean 12.5 years), 548 (26.0%) patients with SLE and 2450 (11.6%) comparators died. A hospitalisation for SLE increased the unadjusted (HR 2.42, 95% CI 2.20 to 2.65) and multivariate-adjusted risk of mortality (aHR 2.03, 95% CI 1.84 to 2.23), which reduced from 1980 to 1999 (aHR 1.42) to 2000-2014 (aHR 1.27). Females (aHR 2.11), Aboriginal Australians (aHR 3.32), socioeconomically disadvantaged (aHR 2.49), and those <40 years old (aHR 7.46) were most vulnerable. At death, patients with SLE had a higher burden of infection (aHR 4.38), CVD (aHR 2.09) and renal disease (aHR 3.43), all p<0.001. CONCLUSIONS: A hospitalisation for SLE associated with an increased risk of mortality over the 1980-2014 period compared with the general population. The risk was especially high in younger (<40 years old), socioeconomically disadvantaged and Aboriginal Australians.


Subject(s)
Lupus Erythematosus, Systemic , Adult , Australia/epidemiology , Cohort Studies , Female , Hospitalization , Humans , Information Storage and Retrieval , Risk Factors
3.
Australas J Ageing ; 39(2): e194-e200, 2020 Jun.
Article in English | MEDLINE | ID: mdl-31742852

ABSTRACT

OBJECTIVES: Transitional care program in Australia targets older patients in hospitals requiring ongoing slow-stream restorative care prior to discharge. Poststroke patients often require extended care and are transferred to these facilities. Transitional care providers require a predicted discharge destination. The aim of this study was to assess the accuracy of this prediction. METHODOLOGY: This study included all patients transferred to transitional care from a stroke rehabilitation unit over eight years. Information regarding the predicted final discharge destination was collected from medical records, and the actual discharge destination was obtained from the transitional care registry. RESULTS: Final destination prediction was equivalent between medical and multidisciplinary teams (κ = 0.87). However, only 60% of the predictions were accurate. Subgroup analysis, as measured by the Modified Barthel Index, suggested that functional gain was a better predictor of final destination. Other characteristics, such as age, sex and type of stroke, did not demonstrate good correlation with the final destination. CONCLUSION: Functional improvement, that is the Modified Barthel Index, is the best predictor of final destination after transitional care.


Subject(s)
Stroke Rehabilitation , Stroke , Transitional Care , Australia , Humans , Patient Discharge , Stroke/diagnosis , Stroke/therapy
SELECTION OF CITATIONS
SEARCH DETAIL
...