Impact of methodological choices in comparative effectiveness studies: application in natalizumab versus fingolimod comparison among patients with multiple sclerosis

Background

Natalizumab and fingolimod are used as high-efficacy treatments in relapsing–remitting multiple sclerosis. Several observational studies comparing these two drugs have shown variable results, using different methods to control treatment indication bias and manage censoring. The objective of this empirical study was to elucidate the impact of methods of causal inference on the results of comparative effectiveness studies.

Methods

Data from three observational multiple sclerosis registries (MSBase, the Danish MS Registry and French OFSEP registry) were combined. Four clinical outcomes were studied. Propensity scores were used to match or weigh the compared groups, allowing for estimating average treatment effect for treated or average treatment effect for the entire population. Analyses were conducted both in intention-to-treat and per-protocol frameworks. The impact of the positivity assumption was also assessed.

Results

Overall, 5,148 relapsing–remitting multiple sclerosis patients were included. In this well-powered sample, the 95% confidence intervals of the estimates overlapped widely. Propensity scores weighting and propensity scores matching procedures led to consistent results. Some differences were observed between average treatment effect for the entire population and average treatment effect for treated estimates. Intention-to-treat analyses were more conservative than per-protocol analyses. The most pronounced irregularities in outcomes and propensity scores were introduced by violation of the positivity assumption.

Conclusions

This applied study elucidates the influence of methodological decisions on the results of comparative effectiveness studies of treatments for multiple sclerosis. According to our results, there are no material differences between conclusions obtained with propensity scores matching or propensity scores weighting given that a study is sufficiently powered, models are correctly specified and positivity assumption is fulfilled.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01623-8.

[The therapeutic contribution of proteomic approaches in cancers]

Up to now, there are no protein tumor markers with a specificity and sensitivity sufficient to have a utility in prognosis and early diagnosis of cancer. Recent advances in proteomics approaches have led to the identification of novel tumor markers of cancer that may have a utility in screening strategies and treatment. The purpose of the current review is to describe the major advances in cancer proteomics, especially those related to the study of serum biomarkers, immune-related responses (autoantibodies) and alterations in cellular proteins.

Proteomics approaches: new technologies and clinical applications in breast carcinomas

Breast cancer is the most diagnosed cancer in women, accounting for approximately 40,000 deaths annually in the USA. In Tunisia, the incidence of breast cancer is approximately 19 new cases per 100,000 women per year. Significant advances have been made in the areas of detection and treatment, but a significant number of breast cancers are detected late. The advent of proteomics provides the hope of discovering novel biological markers that can be used for early detection, prognosis, diagnosis, and therapy. Several proteomics technologies have been used to uncover molecular mechanisms associated with breast.

INTRODUCTION

Breast cancer is a major health problem and one of the leading causes of death among women worldwide. Its incidence is steadily rising in developing countries. In Tunisia, the incidence of breast cancer is approximately 19 new cases per 100,000 women per year(1). Invasive carcinomas represent 70-80% of all breast cancer and among these, infiltrating ductal carcinomas (IDCA) are the most aggressive forms and have a poor prognosis(2). Histopathologically identical breast cancers show a different biological behavior in terms of aggressiveness, progression, and response to therapy. Thus, there is a great need for new breast cancer biomarkers that might help detect this cancer at an earlier stage, to uncover prognostically distinct subclasses, and to provide best individual treatment(2). Currently, the search for specific cancer-related alterations are largely carcinoma at the global level to discover protein patterns that distinguish disease and disease-free states with high sensitivity and specificity. Two dimensional gel electrophoresis coupled with mass spectrometry constitute a new proteomics based paradigm for detecting disease in pathology specimens and monitoring disease response to therapy. This review describes these proteomics technologies and their application in the analysis of breast carcinoma.