The secret of immortal time bias in epidemiologic studies.

نویسندگان

  • Salimah Z Shariff
  • Meaghan S Cuerden
  • Arsh K Jain
  • Amit X Garg
چکیده

In the March 2007 issue of JASN, Hemmelgarn et al.1 reported a 50% reduction in the risk for all-cause mortality for patients who had chronic kidney disease (CKD) and attended multidisciplinary care (MDC) clinics compared with those who received usual care. Their survival curves showed a clear divergence in rates of death between the two groups in the first 6 mo of follow-up. We suggest that it is less plausible from a biologic perspective that use of MDC clinics immediately reduces the short-term risk for death. Rather, much of the early observed effect may be due to survivor treatment selection bias, also known as immortal time bias. Here we consider this issue. In the Hemmelgarn study, a retrospective cohort of 187 clinic patients who were exposed to a MDC clinic were matched to 187 non-MDC clinic control patients to examine the association between MDC and survival.1 Control subjects were chosen on the basis of propensity matching, whereby individuals in the control group had a similar likelihood of being referred to a MDC clinic as those in the MDC clinic group. Figure 1 shows a schematic of how patients with CKD entered the cohort. All patients were required to have an outpatient serum creatinine test performed between July 1 and December 31, 2001. Patients in the MDC clinic group were also required to have attended a MDC clinic between July 1, 2001, and December 31, 2002. The primary analysis for the study was the association between MDC clinic visits and survival, modeled using a Cox regression analysis. Survival time was measured starting from each patient’s serum creatinine test date. In other words, the date of each patient’s serum creatinine represented the date they entered the cohort, or time 0. Patients were followed until the end of the assessment (December 31, 2004) or death, whichever came first. A difference in survival between the two groups was illustrated using Kaplan-Meier survival curves (Figure 2). In this analysis, censoring occurred only at the end of assessment; therefore, the curves essentially represent the proportion of patients who were still alive at each time during follow-up. The curves were step-like in shape, and a dip in the curve occurred when a patient in that group died.2 As can be seen from Figure 2, the curves diverged almost immediately, with the non-MDC clinic curve dipping below the MDC clinic curve, signifying an increased death rate for the non-MDC control group. The difference in the proportion of individuals alive between the two groups steadily increased until about 1.5 yrs, after which point the rate of decline was similar between the groups. The difference in curves was tested using a log-rank test and found to be highly significant (P 0.008). The Cox model yielded a risk reduction of 50% with 95% confidence limits ranging from 29 to 65%. Is this result biologically plausible? From a mechanistic perspective, we suggest that it is less plausible that attending MDC clinics confers an immediate survival advantage over regular care for elderly patients with CKD. These clinics concentrate on better education, lifestyle modification, and medical management over that provided in routine care. Although better efforts at smoking cessation, weight management, dietary protein restriction, glycemic control, renin-angiotensin blockade, BP lowering, and statin use all could improve survival in this high-risk population, practical experience suggests that such a benefit would likely take longer to manifest.3– 6 It is also improbable that better potassium control explains the large early survival benefit. Much of the early observed beneficial effect may be due to survivor treatment selection bias,7 more recently described as immortal time bias.8 First noted in 1885,9 the bias explains the suggestion that Popes seem to live longer than artists10 or Oscar winners longer than nonwinners.11 In general, such individu-

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Practice of Epidemiology Immortal Time Bias in Pharmacoepidemiology

Immortal time is a span of cohort follow-up during which, because of exposure definition, the outcome under study could not occur. Bias from immortal time was first identified in the 1970s in epidemiology in the context of cohort studies of the survival benefit of heart transplantation. It recently resurfaced in pharmacoepidemiology, with several observational studies reporting that various med...

متن کامل

Methodological issues of confounding in analytical epidemiologic studies

Background: Confounding can be thought of as mixing the effect of exposure on the risk of disease with a third factor which distorts the measure of association such as risk ratio or odds ratio. This bias arises because of complex functional relationship of confounder with both exposure and disease (outcome). In this article, we provided a conceptual framework review of confounding issues in epi...

متن کامل

Confounding of the association between statins and Parkinson disease: systematic review and meta-analysis.

PURPOSE Both statins and higher serum cholesterol have been reported to reduce to risk of Parkinson Disease (PD). Given the importance of adjusting for cholesterol levels when evaluating the effect of statins, we assessed whether the protective effect of statins would remain when adjustment for cholesterol is performed. METHODS We conducted a systematic review of epidemiologic studies that re...

متن کامل

Inhaled corticosteroids in chronic obstructive pulmonary disease: results from two observational designs free of immortal time bias.

RATIONALE Recent cohort studies in chronic obstructive pulmonary disease (COPD) have questioned the validity of previously reported associations between inhaled corticosteroids (ICS) and reductions in mortality and rehospitalization in observational studies. Using time-dependent versions of statistical survival models, these studies have suggested immortal time bias as responsible for the propo...

متن کامل

Comment on: Suissa and Azoulay. Metformin and the Risk of Cancer: Time-Related Biases in Observational Studies. Diabetes Care 2012;35:2665–2673

In a recent article in Diabetes Care, Suissa and Azoulay (1) concluded that the impressive results of the metformin-associated reduced cancer risk were due to many researchers failing to adjust for immortal time bias and not using time-dependent analysis of drug exposure. However, this conclusion is not justified since it remains controversial whether immortal time would introduce substantial b...

متن کامل

Response to Yang and Chan. Metformin and the Risk of Cancer: Time-Related Biases in Observational Studies. Diabetes Care 2012;35:2665–2673

Y ang and Chan (1) express uncertainty regarding immortal time bias, an established and rigorously founded principle in epidemiology and statistical sciences, and use data from the Hong Kong Diabetes Registry to quantify the effect of statin use on cardiovascular outcomes. Using the time-fixed approach, known to introduce immortal time bias, they find that statin use is associated with a 34% re...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Journal of the American Society of Nephrology : JASN

دوره 19 5  شماره 

صفحات  -

تاریخ انتشار 2008