The application relates to the technical field of
medical systems, and particularly discloses a construction method of a
cancer cachexia prognosis
composite index CCAR based on a combination of
creatinine and CAR, which comprises the following steps: S1, obtaining serum biomarker data of a
cancer cachexia patient, including
creatinine, C-reactive
protein and
albumin; S2, calculating a C-reactive
protein to
albumin ratio CAR=CRP /
Albumin; S3, taking CAR and Cr as input features, and constructing a nonlinear
composite index CCAR through a
random forest machine learning model; and S4, developing a network
calculator system; the CCAR index constructed by the application can comprehensively reflect the inflammatory burden,
metabolic state and immune level of a
cancer cachexia patient, can provide more accurate
survival prognosis prediction compared with traditional indexes, and the parameters, such as
creatinine, C-reactive
protein to
albumin ratio, contained in the CCAR index are all common blood examination items in clinical practice, so that the CCAR index is convenient to obtain and can be widely applied in clinical practice.