Descriptive statistics of dataset from the meta-analysis and meta-regression analysis on prognostic significance of pre-treatment systemic hemato-immunological indices of cervical cancer patients
Description
We implemented quantitative meta-analyses and time series meta-regression analysis to determine whether systemic hemato-immunological indices, such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), thrombocyte-to-lymphocyte ratio (TLR), and C-reactive protein/albumin ratio (CAR) are associated with an increased risk of cervical collision cancer. The meta-analysis was conducted with a random-effects model using the Review Manager software (Revman version 5.3). The overall survival (OS), disease-free survival (DFS), and progression-free survival (PFS) data were compared among each observational study. All data are expressed as hazard ratios (HRs) and 95% confidence intervals (CIs), and were calculated using the generic inverse of variance method. The logistic meta-regression analyses show novel associations between systemic hemato-immunological indices and risk of cervical collision cancer, underscoring the efficacy and accuracy of this analysis. Likewise, the risk for cervical collision cancer were significantly affected by other parameters such as age and number of patients. This dataset could be useful for medical oncologists, physician scientists, and related scientific communities to implement tumor hemato-immunological indices as promising predicative biomarker in cervical cancer patients. This may ultimately help improve treatment planning strategies. Code used to produce all items in this paper is included in the file entitled “DIBcode.R.” All code used to produce. all dataset in this paper are available in the supplementary file and R datasets package.