L’imputation multiple des données manquantes aléatoirement : concepts généraux et présentation d’une méthode Monte-Carlo

BackgroundStatistical analysis of a data set with missing data is a frequent problem to deal with in epidemiology. Methods are available to manage incomplete observations, avoiding biased estimates and improving their precision, compared to more traditional methods, such as the analysis of the sub-sample of complete observations.MethodsOne of these approaches is multiple imputation, which consists in imputing successively several values for each missing data item. Several completed data sets having the same distribution characteristics as the observed data (variability and correlations) are thus generated. Standard analyses are done separately on each completed dataset then combined to obtain a global result. In this paper, we discuss the various assumptions made on the origin of missing data (at random or not), and we present in a pragmatic way the process of multiple imputation. A recent method, Multiple Imputation by Chained Equations (MICE), based on a Monte-Carlo Markov Chain algorithm under missing at random data (MAR) hypothesis, is described. An illustrative example of the MICE method is detailed for the analysis of the relation between a dichotomous variable and two covariates presenting MAR data with no particular structure, through multivariate logistic regression.ResultsCompared with the original dataset without missing data, the results show a substantial improvement of the regression coefficient estimates with the MICE method, relatively to those obtained on the dataset with complete observations.ConclusionThis method does not require any direct assumption on joint distribution of the variables and it is presently implemented in standard statistical software (Splus, Stata). It can be used for multiple imputation of missing data of several variables with no particular structure.     

Lien précarité – durée et complexité des séjours hospitaliers en secteur de court séjour

BackgroundSeveral studies have shown that socioeconomic deprivation is associated with increased hospitalization lengths of stay (LOS) and costs. Yet, the French DRG-based information system (PMSI) does not take deprived situations into account. Hence, we aimed at extracting routinely available variables measuring deprivation from the Hospital Information System and at assessing their association with severity of illness and hospital LOS.MethodsWe performed record linkage between the PMSI database concerning stays of patients aged more than 16 years in the short-stay sector of Assistance publique–Hôpitaux de Paris in 2007 and an administrative database which provided the following deprivation measures: recipients of Couverture Médicale Universelle (basic or complementary health insurances adapted for underprivileged French citizens) or Aide Médicale d’État (health and medical emergency insurances adapted for underprivileged non French citizens living in France) and homeless patients. We compared length of stays showing a deprivation measure to others after adjustment on morbidity, age and sex.ResultsAmong 352,721 stays, the prevalence of the deprivation measures ranged from 0.71% for “homelessness” to 6.24% for complementary Couverture Médicale Universelle. Stays showing a deprivation measure had specific illnesses and had more frequently associated comorbidities or complications than others. After adjustment, deprivation measures were associated with significantly increased LOS (by 5% for Couverture Médicale Universelle to 48% for emergency Aide Médicale d’État.ConclusionRoutine extraction of deprivation measures from Hospital Information Systems is feasible. Age, sex and illness being equal, these deprivation measures were associated with more complicated cases and increased LOS. We recommend that case mix-based hospital prospective payment systems take socioeconomic deprivation into account.     

Local excision for ypT2 rectal cancer--much ado about something.

BACKGROUND: The role of local excision for pT2 distal rectal cancer has been challenged because of the observation of high rates of lymph node metastases and local failure. However, neoadjuvant chemoradiation therapy (CRT) has led to increased local disease control and significant tumor downstaging, possibly decreasing rates of lymph node metastases. In this setting, a possible role for local excision of ypT2 has been suggested. METHODS: A total of 401 patients with distal rectal cancer underwent neoadjuvant CRT. Tumor response assessment was performed after at least 8 weeks from CRT completion. One hundred and twelve patients with complete clinical response were not immediately operated on and were excluded from the study, and 289 patients with incomplete clinical response were managed by radical surgery. Patients with final pathological stage ypT2 were analyzed to determine the risk of unfavorable pathological features that could represent unacceptable risk for local failure after local excision. RESULTS: Eighty-eight (30%) patients had ypT2 rectal cancer. Final ypT status was not associated with pretreatment radiological staging (p = 0.62). ypT status was significantly associated with the risk of lymph node metastases, risk of perineural and vascular invasion, and recurrence (p = 0.001). Lymph node metastases were present in 19% of patients with ypT2 rectal cancer. The risk of lymph node metastases in ypT2 was associated with the presence of perineural invasion (47% vs 4%; p = <0.001), vascular invasion (59% vs 6%; p < 0.001), and decreased mean interval CRT surgery (12 vs 18 weeks; p < 0.001), but not with mean tumor size (3.2 vs 3.1 cm; p = 0.8). Disease-free and overall survival rates were significantly better for patients with ypT2N0 (p = 0.02 and 0.006, respectively). Fifty-five (63%) patients with ypT2 had at least one unfavorable pathological feature for local excision (lymph node metastases, vascular or perineural invasion, mucinous type or tumor size >3 cm). CONCLUSION: Lymph node metastases were present in 19% of patients with ypT2 and were significantly associated with poor overall and disease-free survival rates. The risk of lymph node metastases could not be predicted by radiological staging or tumor size. Radical surgery should be considered the standard treatment option for ypT2 rectal cancer after CRT.