[Evaluation of thoracic surgical practice. The impact of specialisation and the effect of volume on the results of cancer treatment: resectability, post-operative mortality, and long-term survival]. / Evaluation des pratiques en chirurgie thoracique.

INTRODUCTION AND METHODS: The impact of the volume of activity and the specialisation of the surgeon and the hospital on the quality of health care for patients with non-small cell lung cancer (NSCLC) was evaluated from the publications over the last 20 years. RESULTS: The statistics, based mainly on administrative data, identified a significant decrease in post operative mortality (5 out of 7 studies) and improved long-term survival (2 out of 3 studies) in establishments undertaking large numbers of lung resections. The threshold for defining high volume groups varied from study to study (from 28 to 128 procedures per year). The same tendency was seen among the surgeons where specialisation in thoracic surgery led to higher levels of resectability and parenchymal preservation. CONCLUSIONS: These results should be interpreted with caution on account of the nature of the data and the methodology employed. A certification of referral centres, validated by the French Thoracic and Cardiovascular Surgical Society, based on the training, level of activity in cancer surgery, and the infrastructure of the hospital should lead to a more even standard of care for patients with NSCLC.

Exploring a physico-chemical multi-array explanatory model with a new multiple covariance-based technique: structural equation exploratory regression.

In this work, we consider chemical and physical variable groups describing a common set of observations (cigarettes). One of the groups, minor smoke compounds (minSC), is assumed to depend on the others (minSC predictors). PLS regression (PLSR) of m inSC on the set of all predictors appears not to lead to a satisfactory analytic model, because it does not take into account the expert's knowledge. PLS path modeling (PLSPM) does not use the multidimensional structure of predictor groups. Indeed, the expert needs to separate the influence of several pre-designed predictor groups on minSC, in order to see what dimensions this influence involves. To meet these needs, we consider a multi-group component-regression model, and propose a method to extract from each group several strong uncorrelated components that fit the model. Estimation is based on a global multiple covariance criterion, used in combination with an appropriate nesting approach. Compared to PLSR and PLSPM, the structural equation exploratory regression (SEER) we propose fully uses predictor group complementarity, both conceptually and statistically, to predict the dependent group.

Event history analysis of groups: the findings of an on-going research project.

PIP: "The event history approach...is applied using individual longitudinal data. Ideally, however, each individual itinerary would be situated in as broad a context as possible, and the analysis of individual demographic processes would take account of the close or competing events affecting the individual's contact circle. In event history modelling, a shift from the individual to their entourage, for both data collection and analysis, implies a reconsideration of the choice of entities for longitudinal monitoring. A compromise must be reached between conceptual operationality and analytical consistency, in terms of both theory and models: this article presents the formal developments, then the more applied results from this on-going research [using French data]." (EXCERPT)^ieng