Variation in centre-specific survival in patients starting renal replacement therapy in England is explained by enhanced comorbidity information from hospitalization data

Background Unadjusted survival on renal replacement therapy (RRT) varies widely from centre to centre in England. Until now, missing data on case mix have made it impossible to determine whether this variation reflects genuine differences in the quality of care. Data linkage has the capacity to reduce missing data. Methods Modelling of survival using Cox proportional hazards of data returned to the UK Renal Registry on patients starting RRT for established renal failure in England. Data on ethnicity, socioeconomic status and comorbidity were obtained by linkage to the Hospital Episode Statistics database, using data from hospitalizations prior to starting RRT. Results Patients with missing data were reduced from 61 to 4%. The prevalence of comorbid conditions was remarkably similar across centres. When centre-specific survival was compared after adjustment solely for age, survival was below the 95% limit for 6 of 46 centres. The addition of variables into the multivariable model altered the number of centres that appeared to be ‘outliers’ with worse than expected survival as follows: ethnic origin four outliers, socioeconomic status eight outliers and year of the start of RRT four outliers. The addition of a combination of 16 comorbid conditions present at the start of RRT reduced the number of centres with worse than expected survival to one. Conclusions Linked data between a national registry and hospital admission dramatically reduced missing data, and allowed us to show that nearly all the variation between English renal centres in 3-year survival on RRT was explained by demographic factors and by comorbidity

Association between glycemia and mortality in diabetic individuals on renal replacement therapy in the U.K.

OBJECTIVE: In the U.K., one-third of patients receiving treatment with dialysis have diabetes. Guidelines from organizations representing patients with renal disease or diabetes advocate tight glycemic control in patients with end-stage renal disease, despite glucose-lowering trials having excluded these patients. RESEARCH DESIGN AND METHODS: Using national U.K. Renal Registry data, we tested whether glycemia as measured by hemoglobin (Hb) A(1c) (HbA(1c)) level is associated with death in adults with diabetes starting hemodialysis or peritoneal dialysis between 1997 and 2006, and observed for at least 6 months. Of 7,814 patients, we excluded those who had died within 6 months; had received transplants; were lost/recovered; or lacked measures of HbA1c, ethnicity, or Hb. Categorizing HbA1c measured in the first 6 months of starting dialysis as 8.5% was 1.5 (1.2-1.9). The projected difference in median survival time between younger patients with a reference HbA1c value versus >8.5% was 1 year. CONCLUSIONS: In the absence of trials, and confounding notwithstanding, these observational data support improved glycemic control in younger patients prior to and during dialysis

Protocol and rationale for the international lung screening trial

Rationale: The NLST (National Lung Screening Trial) reported a 20% reduction in lung cancer mortality with low-dose computed tomography screening; however, important questions on how to optimize screening remain, including which selection criteria are most accurate at detecting lung cancers and what nodulemanagement protocol is most efficient. The PLCOm2012 (Prostate, Lung, Colorectal and Ovarian) Cancer Screening Trial 6-year and PanCan (Pan-Canadian Early Detection of Lung Cancer) nodule malignancy risk models are two of the better validated risk prediction models for screenee selection and nodule management, respectively. Combined use of these models for participant selection and nodule management could significantly improve screening efficiency. Objectives: The ILST (International Lung Screening Trial) is a prospective cohort study with two primary aims: 1) Compare the accuracy of the PLCOm2012 model against U.S. Preventive Services Task Force (USPSTF) criteria for detecting lung cancers and 2) evaluate nodule management efficiency using the PanCan nodule probability calculator-based protocol versus Lung-RADS. Methods: ILST will recruit 4,500 participants who meet USPSTF and/ or PLCOm2012 risk 651.51%/6-year selection criteria. Participants will undergo baseline and 2-year low-dose computed tomography screening. Baseline nodules are managed according to PanCan probability score. Participants will be followed up for a minimum of 5 years. Primary outcomes for aim 1 are the proportion of individuals selected for screening, proportion of lung cancers detected, and positive predictive values of either selection criteria, and outcomes for aim 2 include comparing distributions of individuals and the proportion of lung cancers in each of three management groups: next surveillance scan, early recall scan, or diagnostic evaluation recommended. Statistical powers to detect differences in the four components of primary study aims were >82%. Conclusions: ILST will prospectively evaluate the comparative accuracy and effectiveness of two promising multivariable risk models for screenee selection and nodule management in lung cancer screening