[Prognostic factor analysis in 203 patients with chronic lymphocytic leukaemia]

Zhonghua Xue Ye Xue Za Zhi. 2009 Jul;30(7):435-9.
[Article in Chinese]

Abstract

Objective: To explore prognostic factors in patients with chronic lymphocytic leukemia (CLL).

Methods: Two hundred and three CLL patients in our hospital between 2000 to 2007 were retrospectively reviewed for prognostic factor analysis. Survival was analysed by Kaplan-Meier analysis, univariate analysis by Log-rank test and multivariate analysis by COX regression model.

Results: With a median follow-up time of 48.0 (3.0-156.0) months, the 5-year overall survival (OS) rate was (87.3 +/- 2.4)% and 10-year OS rate was (77.4 +/- 3.3)%. Forty-eight (23.6%) patients died. Univariate analysis indicated that advanced clinical stage, B symptoms, extranodal involvement, number of lymph node regions involved > or = 3, enlarged liver, Hb < 100 g/L, BPC < 100 x 10(9)/L, absolute lymphocyte count (ALC) > 50 x 10(9)/L, atypical cell morphology, progression to stage, non-response to treatment, complicating infections and secondary cancer or disease transformation were associated with poor prognosis. And on multivariate analysis, lymph node region involved > or = 3 and atypical cell morphology were independent poor prognostic factors. Based on the two independent poor prognostic factors, three risk groups were defined: low--(0 factor), intermediate--(one factor) and high--(two factors) groups. The 5 year OS rates were (89.8 +/- 3.5)%, (66.4 +/- 7.2)% and (15.0 +/- 13.8)%, respectively, and the difference between them was statistically.

Conclusion: The number of lymph node region involved and cell morphology are useful for assessing CLL patients prognosis.

Publication types

  • English Abstract
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Female
  • Follow-Up Studies
  • Humans
  • Kaplan-Meier Estimate
  • Leukemia, Lymphocytic, Chronic, B-Cell* / pathology
  • Lymph Nodes / pathology
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Prognosis
  • Proportional Hazards Models
  • Retrospective Studies