The relationships between systemic cytokine profiles and inflammatory markers in colorectal cancer and the prognostic significance of these parameters

Background Immunomodulatory cytokines and systemic inflammatory markers are important during cancer development and progression. This study investigated the association and prognostic impact of systemic cytokine profiles and inflammatory markers in colorectal cancer (CRC). Methods Interleukin (IL)-1β, IL-6, IL-8, IL-9, IL-10, tumour necrosis factor (TNF)-α and vascular endothelial growth factor (VEGF) serum levels were measured using multiplex bead assays in CRC patients. Data on systemic inflammatory markers, such as the modified Glasgow prognostic score (mGPS), the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), prognostic nutritional index (PNI) and fibrinogen, were collected. Survival analysis was performed to identify factors associated with progression-free survival (PFS) and overall survival (OS). Results There were moderate-to-strong correlations within serum cytokines, as well as within systemic inflammatory markers, whereas the associations between serum cytokines and systemic inflammatory markers were generally weak. IL-8 and the LMR were independent significant prognostic factors for PFS and OS. The low IL-8 and high LMR group had the best survival (both PFS and OS) of all groups. Conclusions Systemic cytokine profiles and inflammatory markers have relatively weak intergroup correlations. A composite classification of systemic cytokine profiles and inflammatory markers has an enhanced prognostic value in CRC.


Specimen characteristics 4
Describe type of biological material used (including control samples) and methods of preservation and storage. Methods (page no. 5) Assay methods 5 Specify the assay method used and provide (or reference) a detailed protocol, including specific reagents or kits used, quality control procedures, reproducibility assessments, quantitation methods, and scoring and reporting protocols. Specify whether and how assays were performed blinded to the study endpoint.

Study design
6 State the method of case selection, including whether prospective or retrospective and whether stratification or matching (e.g., by stage of disease or age) was used. Specify the time period from which cases were taken, the end of the follow-up period, and the median follow-up time.
Methods (page no. 5) 7 Precisely define all clinical endpoints examined. Methods (page no. 10) 8 List all candidate variables initially examined or considered for inclusion in models. Methods (page no. 5,6) 9 Give rationale for sample size; if the study was designed to detect a specified effect size, give the target power and effect size.
Methods (page no. 10) Statistical analysis methods Specify all statistical methods, including details of any variable selection procedures and other model-building issues, how model assumptions were verified, and how missing data were handled. Methods (page no. 10) Methods (page no. 10)

11
Clarify how marker values were handled in the analyses; if relevant, describe methods used for cutpoint determination.

Data 12
Describe the flow of patients through the study, including the number of patients included in each stage of the analysis (a diagram may be helpful) and reasons for dropout. Specifically, both overall and for each subgroup extensively examined report the numbers of patients and the number of events.
Results (page no. 10) Results (page no. 10) Table 1 13 Report distributions of basic demographic characteristics (at least age and sex), standard (disease-specific) prognostic variables, and tumor marker, including numbers of missing values.

Analysis and presentation 14
Show the relation of the marker to standard prognostic variables. Results (page no. 12) Supplementary Table 7  15 Present univariable analyses showing the relation between the marker and outcome, with the estimated effect (e.g., hazard ratio and survival probability). Preferably provide similar analyses for all other variables being analyzed. For the effect of a tumor marker on a time-to-event outcome, a Kaplan-Meier plot is recommended. Table 3 16 For key multivariable analyses, report estimated effects (e.g., hazard ratio) with confidence intervals for the marker and, at least for the final model, all other variables in the model. Table 4 17 Among reported results, provide estimated effects with confidence intervals from an analysis in which the marker and standard prognostic variables are included, regardless of their statistical significance.
Results (page no. 11) 18 If done, report results of further investigations, such as checking assumptions, sensitivity analyses, and internal validation.

19
Interpret the results in the context of the pre-specified hypotheses and other relevant studies; include a discussion of limitations of the study.
Discussion (page no. 13-15) 20 Discuss implications for future research and clinical value. Discussion (page no. 15)