List of the Clinical Variables Analyzed With a Univariate Technique in Relation to OS, RFS, and FFS
Clinical Variables . | OS (P) . | RFS (P) . | FFS (P) . |
---|---|---|---|
Sex5-150 | .1744 | .5736 | .5230 |
Age5-151 | 4 × 10−5 | .1118 | .0034 |
Histology ([LP + NS] v MC v LD) | .0065 | .0019 | .0013 |
Stage (II v III v IV) | .1566 | .2503 | .2607 |
Systemic symptoms5-150 | .7488 | .5736 | .7723 |
Karnofsky index5-151 | .0003 | .2020 | .0085 |
Bulky disease5-150 | .6047 | .6805 | .4041 |
Bone marrow involvement5-150 | .0005 | .0472 | .0077 |
Visceral involvement5-150 | .8196 | .7952 | .8052 |
ESR5-151 | .7235 | .5916 | .5435 |
Hb5-151 | .1795 | .7675 | .6559 |
LDH5-151 | .5742 | .6926 | .5763 |
Serum albumin5-151 | .6649 | .3793 | .8086 |
DI of CT cycles 1 to 35-151 | .0346 | .6931 | .3905 |
DI of whole CT5-151 | .6236 | .6900 | .3691 |
Radiotherapy5-150 | .6242 | .5227 | .4193 |
SLNG prognostic index5-151 | .0006 | .1972 | .0396 |
IDHD 5-yr OS estimate5-151 | 7 × 10−5 | .0371 | .0007 |
Clinical Variables . | OS (P) . | RFS (P) . | FFS (P) . |
---|---|---|---|
Sex5-150 | .1744 | .5736 | .5230 |
Age5-151 | 4 × 10−5 | .1118 | .0034 |
Histology ([LP + NS] v MC v LD) | .0065 | .0019 | .0013 |
Stage (II v III v IV) | .1566 | .2503 | .2607 |
Systemic symptoms5-150 | .7488 | .5736 | .7723 |
Karnofsky index5-151 | .0003 | .2020 | .0085 |
Bulky disease5-150 | .6047 | .6805 | .4041 |
Bone marrow involvement5-150 | .0005 | .0472 | .0077 |
Visceral involvement5-150 | .8196 | .7952 | .8052 |
ESR5-151 | .7235 | .5916 | .5435 |
Hb5-151 | .1795 | .7675 | .6559 |
LDH5-151 | .5742 | .6926 | .5763 |
Serum albumin5-151 | .6649 | .3793 | .8086 |
DI of CT cycles 1 to 35-151 | .0346 | .6931 | .3905 |
DI of whole CT5-151 | .6236 | .6900 | .3691 |
Radiotherapy5-150 | .6242 | .5227 | .4193 |
SLNG prognostic index5-151 | .0006 | .1972 | .0396 |
IDHD 5-yr OS estimate5-151 | 7 × 10−5 | .0371 | .0007 |
The reported levels of statistical significance derive from a log-rank test for qualitative variables and from a likelihood ratio test in a proportional hazards regression model for quantitative variables.
Binary data, ie, present (male, given) or absent (female, not given).
Data used in a continuous distribution.