Skip to main content
Journal cover image

98% IGHV gene identity is the optimal cutoff to dichotomize the prognosis of Chinese patients with chronic lymphocytic leukemia.

Publication ,  Journal Article
Shi, K; Sun, Q; Qiao, C; Zhu, H; Wang, L; Wu, J; Wang, L; Fu, J; Young, KH; Fan, L; Xia, Y; Xu, W; Li, J
Published in: Cancer Med
February 2020

Immunoglobulin heavy chain variable region (IGHV) mutational status has been an important prognostic factor for chronic lymphocytic leukemia (CLL) for decades. Patients with unmutated IGHV (≥98% identity to the germline sequence) have inferior prognosis and tend to carry unfavorable genetic markers compared to those with mutated IGHV (<98% identity to the germline sequence). However, 98% as the cutoff for IGHV mutational status is a mathematical choice and remains controversial. We have previously reported distinct IGHV repertoire features between Chinese and western CLL populations. Here, we retrospectively studied 595 Chinese CLL patients to determine the best cutoff value for IGHV in Chinese CLL population. Using 1% as the interval for IGHV identity, we divided the studied cohort into seven subgroups from 95% to 100%. Briefer time to first treatment (TTFT) and overall survival (OS) were observed in cases with ≥98% compared to those with <98%, while the differences were obscure within subgroups ≥98% (98%-98.99%, 99%-99.99%, and 100%) and <98% (<94.99%, 95%-95.99%, 96%-96.99%, and 97%-97.99%). Multivariate analysis confirmed the independent prognostic value of 98% being the cutoff for IGHV identity in terms of both TTFT and OS. All the prognostic factors, including del(17p13), del(11q22.3), TP53 mutation, MYD88 mutation, NOTCH1 mutation, SF3B1 mutation, CD38, ZAP-70, Binet staging, gender, and β2-microglobulin, were significantly different in distribution between group <98% and group ≥98%, but not among subgroups 98%-98.99%, 99%-99.99%, and 100%. In conclusion, 98% is the optimal cutoff of IGHV identity for the prognosis evaluation of Chinese CLL patients.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Cancer Med

DOI

EISSN

2045-7634

Publication Date

February 2020

Volume

9

Issue

3

Start / End Page

999 / 1007

Location

United States

Related Subject Headings

  • Young Adult
  • Treatment Outcome
  • Rituximab
  • Risk Assessment
  • Retrospective Studies
  • Reference Values
  • Prognosis
  • Mutation
  • Middle Aged
  • Male
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Shi, K., Sun, Q., Qiao, C., Zhu, H., Wang, L., Wu, J., … Li, J. (2020). 98% IGHV gene identity is the optimal cutoff to dichotomize the prognosis of Chinese patients with chronic lymphocytic leukemia. Cancer Med, 9(3), 999–1007. https://doi.org/10.1002/cam4.2788
Shi, Ke, Qian Sun, Chun Qiao, Huayuan Zhu, Li Wang, Jiazhu Wu, Lili Wang, et al. “98% IGHV gene identity is the optimal cutoff to dichotomize the prognosis of Chinese patients with chronic lymphocytic leukemia.Cancer Med 9, no. 3 (February 2020): 999–1007. https://doi.org/10.1002/cam4.2788.
Shi K, Sun Q, Qiao C, Zhu H, Wang L, Wu J, et al. 98% IGHV gene identity is the optimal cutoff to dichotomize the prognosis of Chinese patients with chronic lymphocytic leukemia. Cancer Med. 2020 Feb;9(3):999–1007.
Shi, Ke, et al. “98% IGHV gene identity is the optimal cutoff to dichotomize the prognosis of Chinese patients with chronic lymphocytic leukemia.Cancer Med, vol. 9, no. 3, Feb. 2020, pp. 999–1007. Pubmed, doi:10.1002/cam4.2788.
Shi K, Sun Q, Qiao C, Zhu H, Wang L, Wu J, Fu J, Young KH, Fan L, Xia Y, Xu W, Li J. 98% IGHV gene identity is the optimal cutoff to dichotomize the prognosis of Chinese patients with chronic lymphocytic leukemia. Cancer Med. 2020 Feb;9(3):999–1007.
Journal cover image

Published In

Cancer Med

DOI

EISSN

2045-7634

Publication Date

February 2020

Volume

9

Issue

3

Start / End Page

999 / 1007

Location

United States

Related Subject Headings

  • Young Adult
  • Treatment Outcome
  • Rituximab
  • Risk Assessment
  • Retrospective Studies
  • Reference Values
  • Prognosis
  • Mutation
  • Middle Aged
  • Male