Classical Kaposi sarcoma : Prognostic factor analysis of 248 patients

✍ Scribed by Baruch Brenner; Alina Weissmann-Brenner; Erica Rakowsky; Sara Weltfriend; Eyal Fenig; Rachel Friedman-Birnbaum; Aaron Sulkes; Shai Linn

• Publisher: John Wiley and Sons
• Year: 2002
• Tongue: English
• Weight: 87 KB
• Volume: 95
• Category: Article
• ISSN: 0008-543X
• DOI: 10.1002/cncr.10907

✦ Synopsis

Background:

Classical kaposi sarcoma (cks) is a rare indolent neoplasm that is particularly prevalent among jews of ashkenazi and mediterranean origin. data regarding prognostic factors for cks are scarce. the aim of the current retrospective analysis was to better define prognostic subgroups among patients with cks.

Methods:

Between 1960 and 1995, 248 consecutive patients with cks were treated at the rambam and rabin medical centers in israel. although treatment options included local excision, radiotherapy, and chemotherapy, observation alone was used for 31% of patients. for prognostic factor analysis, disease progression was classified as any progression and dissemination, and progression-free survival was calculated for each.

Results:

At a median follow-up of 20 months, four patients (1.6%) died of cks. of the patients eligible for analysis, 94 of 220 (39%) had any progression and 23 of 120 (18%) had dissemination. only 8 of 202 (4%) had visceral spread. on univariate analysis, age was a statistically significant prognostic factor for any progression (p = 0.04), whereas immunosuppression and visceral involvement at presentation had only borderline significance. immunosuppression was the only prognostic factor for dissemination (p = 0.003). on multivariate analysis, both age and immunosuppression were significant prognostic factors for any progression (p = 0.001 and 0.01, respectively). immunosuppression was also predictive of dissemination (p = 0.006).

Conclusions:

Immunosuppression and older age (50 years and older) are strongly associated with poorer outcome among cks patients. the two end points used in this study may be used for future prognostic factor analyses.