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Identification of Remaining Life Expectancy Less Than Two Weeks by C-Reactive Protein/Albumin Ratio, Prognostic Nutritional Index, Fibrosis-4 Index, and Albumin-Bilirubin Score in Terminal Cancer Patients.

Shoko IedaTomoyoshi MiyamotoKouichi HosomiManabu TakegamiAtsufumi Kawabata
Published in: Journal of palliative medicine (2021)
Background: Accurate prognosis in terminal cancer patients is useful to improve their quality of life and also to decide the cessation of fluid administration. Nonetheless, few prognostic indicators are available for prediction of such a short-term life expectancy. Objectives: The present study aimed at evaluating the efficacy of C-reactive protein (CRP)/albumin (CRP/Alb) ratio, prognostic nutritional index (PNI), fibrosis-4 (FIB-4) index, and albumin-bilirubin (ALBI) score in identifying terminal cancer patients who have a life expectancy less than two weeks. Design: Retrospective study. Setting/Subjects: Of 483 patients who died between April 2019 and March 2020 at a single center in Japan, 102 who met the inclusion criteria were enrolled in this study. Measurements: CRP/Alb, PNI, FIB-4, and ALBI were calculated from the laboratory data collected 1-13, 14-27, 28-83, and 168-365 days before death and subjected to statistical analyses. Results: CRP/Alb, PNI, FIB-4, and ALBI values were significantly associated with the time before death during terminal 365 days. CRP/Alb ≥4.4, PNI <30, FIB-4 ≥ 9.4, and ALBI ≥ -1.26 were significantly associated with the transition from the first half to the second half of terminal four weeks. Of those prognostic indicators, three and four combinations provided significantly reliable estimation of a life expectancy less than two weeks. Conclusions: CRP/Alb, PNI, FIB-4, ALBI, and their combinations are considered to help identify cancer patients who have a life expectancy less than two weeks, which is useful to make appropriate end-stage treatment decisions, for example, cessation of artificial hydration therapy.
Keyphrases
  • liver fibrosis
  • gestational age
  • electronic health record
  • bone marrow
  • high resolution
  • tyrosine kinase
  • mesenchymal stem cells
  • big data
  • artificial intelligence
  • bioinformatics analysis