Table 5. Univariate and multivariate logistic regression analysis of continuous blood counts on the survival rate within the first 6 months.
Univariate Logistic Model | Multivariate Logistic Model* | |||||
---|---|---|---|---|---|---|
Baseline risk | Coefficient (β) | SD | P-value | Coefficient (β) | SD | P-value |
Log (ARC+1) | 0.4855 | 0.1410 | 0.0006 | -0.2022 | 0.1719 | < 0.2394 |
Log (ALC+1) | 0.7711 | 0.2396 | 0.0013 | ------ | ------ | ------ |
Log (ANC+1) | 0.7571 | 0.1152 | < 0.0001 | 0.8755 | 0.1586 | < 0.0001 |
Log (Plt+1) | 0.1425 | 0.2375 | 0.5485 | ------ | ------ | ------ |
Log (PNH+1) | 0.4362 | 0.4404 | 0.3219 | ------ | ------ | ------ |
Log (Age+1) | -0.7244 | 0.3351 | 0.0306 | ------ | ------ | ------ |
Stepwise regression with multivariate logistic models returns three log transformed covariates: ANC, Plt and PNH.
------ Variable deleted by the stepwise procedure.
ARC, absolute reticulocyte count; ALC, absolute lymphocyte count, ANC, absolute neutrophil count; PNH, paroxysmal nocturnal haemoglobinuria; Plt, platelet count.