Prognostic Value of Immune Interaction Index

In order to represent a weight of the interaction between inflammatory pro-tumour populations (i.e. neutrophils, platelets and monocytes) and anti-cancer immune populations (i.e. lymphocytes), PIV was calculated as: [neutrophil count (10³/mmc) × platelet count (10³/mmc) × monocyte count (10³/mmc)]/lymphocyte count (10³/mmc). Maximally selected rank statistics method for PFS was used to find an optimal cut-off value^{13 (link)} to stratify patients in low PIV vs high PIV. NLR was calculated as: neutrophil count (10³/mmc)/lymphocyte count (10³/mmc). NLR was defined high if >3, platelet count was defined high if >310 × 10³/mmc and monocyte count was defined high if >0.5 × 10³/mmc based on literature data.^{6 (link)–8 (link)} SII was calculated as [neutrophil count (10³/mmc) × platelet count(10³/mmc)/lymphocyte count (10³/mmc) and defined high if >730 based on literature data.^{10 (link)}Fisher exact test, Chi-square test, Mann–Whitney U test or Kruskal-Wallis test, as appropriate, were used to analyse the association between baseline PIV and the other clinicopathological characteristics. PFS was defined as the time from randomisation to disease progression or death from any cause. OS was defined as the time from randomisation to death from any cause. Generalised boosted regression was used to screen the association of PIV and the other IIBs with PFS and OS.^{14 (link),15 (link)} Further survival analyses were performed using the Kaplan–Meier method and the Cox proportional hazards regression models. All the variables showing a P below the significance threshold in the univariate models were included in a multivariable model. The variables showing a P below the significance threshold in the multivariable models were considered to be independent prognostic factors. All tests were 2-sided with a significance threshold of 0.05. Statistical analyses were performed using the R (version 3.5.0) and R Studio (version 1.1.447).

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Fucà G., Guarini V., Antoniotti C., Morano F., Moretto R., Corallo S., Marmorino F., Lonardi S., Rimassa L., Sartore-Bianchi A., Borelli B., Tampellini M., Bustreo S., Claravezza M., Boccaccino A., Murialdo R., Zaniboni A., Tomasello G., Loupakis F., Adamo V., Tonini G., Cortesi E., de Braud F., Cremolini C, & Pietrantonio F. (2020). The Pan-Immune-Inflammation Value is a new prognostic biomarker in metastatic colorectal cancer: results from a pooled-analysis of the Valentino and TRIBE first-line trials. British Journal of Cancer, 123(3), 403-409.

Publication 2020

Cancer Disease progression Inflammatory Lymphocyte count Lymphocytes Monocyte Neutrophil Patients Platelet count Platelets Populations Prognostic factors Tumour

Corresponding Organization :

Other organizations : Fondazione IRCCS Istituto Nazionale dei Tumori, University of Pisa, Azienda Ospedaliera Universitaria Pisana, Istituto Oncologico Veneto, Humanitas University, Istituti di Ricovero e Cura a Carattere Scientifico, Azienda Socio Sanitaria Territoriale Grande Ospedale Metropolitano Niguarda, Ospedale San Luigi Gonzaga, Azienda Ospedaliera Citta' della Salute e della Scienza di Torino, Ente Ospedaliero Ospedali Galliera, Ospedale Policlinico San Martino, University of Genoa, Fondazione Poliambulanza Istituto Ospedaliero, Istituti Ospitalieri di Cremona, Azienda Ospedaliera Ospedali Riuniti Papardo Piemonte, Campus Bio Medico University Hospital, Policlinico Umberto I, University of Milan

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Variable analysis

independent variables

Neutrophil count (10^3/mmc)
Platelet count (10^3/mmc)
Monocyte count (10^3/mmc)
Lymphocyte count (10^3/mmc)
NLR (neutrophil count/lymphocyte count)
Platelet count (defined high if >310 x 10^3/mmc)
Monocyte count (defined high if >0.5 x 10^3/mmc)
SII (neutrophil count x platelet count/lymphocyte count)

dependent variables

PIV ([neutrophil count x platelet count x monocyte count]/lymphocyte count)
PFS (progression-free survival)
OS (overall survival)

control variables

None explicitly mentioned

controls

None explicitly mentioned

Annotations

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