Open AccessExternal validation of the prognostic relevance of the advanced lung cancer inflammation index (ALI) in pancreatic cancer patients
Author(s) -
Barth Dominik Andreas,
Brenner Carina,
Riedl Jakob Michael,
Prinz Felix,
Klocker Eva Valentina,
Schlick Konstantin,
Kornprat Peter,
Lackner Karoline,
Stöger Herbert,
Stotz Michael,
Gerger Armin,
Pichler Martin
Publication year - 2020
Publication title -
cancer medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 53
ISSN - 2045-7634
DOI - 10.1002/cam4.3233
Subject(s) - medicine , proportional hazards model , lung cancer , oncology , pancreatic cancer , hazard ratio , gastroenterology , stage (stratigraphy) , cancer , cohort , chemoradiotherapy , multivariate analysis , biomarker , body mass index , confidence interval , paleontology , biochemistry , chemistry , biology
Background The advanced lung cancer inflammation index (ALI) was first introduced for prognosis prediction in lung cancer patients and since then evaluated in several other malignancies. However, in pancreatic cancer (PC) the ALI and its prognostic utility were only investigated in a comparably small and specific cohort of locally advanced PC patients treated with chemoradiotherapy. Methods In our single‐center cohort study, we included 429 patients with histologically verified PC who were treated between 2003 and 2015 at our academic institution. The ALI was defined as body mass index (BMI; kg/m 2 ) × serum albumin levels (g/dL)/neutrophil‐lymphocyte ratio (NLR) and we defined the optimal cutoff for biomarker dichotomization by ROC‐analysis. Kaplan‐Meier method as well as uni‐ and multivariate Cox regression Hazard proportional models were implemented to assess the prognostic potential of ALI in PC patients. We considered cancer‐specific survival (CSS) as the primary endpoint of the study. Results The ALI showed a significant negative correlation with CA19‐9 levels and C‐reactive protein levels whereas we found an association with localized tumor stage and better performance status ( P < .05 for all mentioned variables). As opposed to patients with a high ALI, decreased ALI was significantly associated with shorter CSS (HR = 0.606, 95% CI: 0.471‐0.779, P = .001). Multivariate analysis demonstrated tumor grade, tumor stage, chemotherapy, C‐reactive protein levels, and CA19‐9 levels to independently predict for CSS (all P < .05). In contrast the ALI failed to independently predict for CSS in the performed multivariate models (HR = 0.878, 95% CI: 0.643‐1.198, P = .411). Conclusion In this large cohort of PC patients, the ALI did not complement existing clinicopathological factors for outcome determination.