NSCLC Prognosis Model Medical Algorithm

Description

Mandrekar et al developed a model for predicting the probability of survival for a patient with advanced non-small cell lung cancer (NSCLC). This can help identify a patient who may benefit from more aggressive or a novel therapy. The authors are from the Mayo Clinic, Missouri Valley Cancer Center (Omaha), Duluth Clinic, University of Manitoba, and University of Colorado.

Patient selection: Stage IV non-small cell lung cancer and ECOG performance scale <= 3

Parameters:

(1) ECOG performance scale (PS)

(2) body weight

(3) anemia

(4) white blood cell (WBC) count

(5) baseline survival S0

Parameter	Finding	Points
ECOG performance	0	0
	1	0.48
	2 or 3	0.96
body weight	underweight	0.60
	normal weight	0
	overweight	0.11
	obese	-0.11
anemia	absent	0
	present	0.41
WBC count	normal	0
	increased	0.35

X =

= (points for ECOG) + (points for body weight) + (points for anemia) + (points for WBC count) + 0.26

Time (Y)	S0
3 months	0.91
6 months	0.76
9 months	0.64
12 months	0.54
18 months	0.39
24 months	0.30

This data can be approximated in Minitab as:

survival factor S0 =

= (0.000999 * ((months)^2)) - (0.05567 * (months)) + 1.063

probability for survival to Y months =

= (S0 for Y months) ^ (EXP(X))

To read more or access our algorithms and calculators, please log in or register.

Description

Specialty

Objective

ICD-10

Prognostic Model of Mandrekar et al for Advanced Non-Small Cell Lung Cancer (NSCLC)

Purpose: To estimate the survival for a patient with advanced non-small cell lung cancer based on the model of Mandrekar et al.

Description

Specialty

Objective

ICD-10