Abstract
Prognostic factors are important for evaluating patients (pts) with CLL, owing to heterogeneity in response to treatment and clinical course. The goal of this analysis was to evaluate the newer prognostic factors in relation to traditional ones in previously untreated pts receiving frontline chemoimmunotherapy. Traditional prognostic factors include age, Rai stage, absolute lymphocyte count (ALC), lymphocyte doubling time, and many others. Newer prognostic factors, include IgVH gene mutation status (MS), chromosome abnormalities by FISH, and leukemia cell expression of ZAP70. Finally, the clinical endpoint is important in considering and evaluating prognostic factors, since significant independent factors can be different for response to treatment, time to progression (TTP), and overall survival (OS).
We evaluate 488 previously untreated pts who had an NCI-WG ‘96 indication for treatment and received frontline chemoimmunotherapy (CIT). Treatment was with a fludarabinebased CIT regimen: FCR (n=300), FCMR (n=30), FCR3 (n=65), FCR+GM-CSF (n=45), or CFAR (n=48). The CR rate, TTP, and OS were not significantly different between the CIT regimens; median follow-up times varied. The overall estimated median follow-up time was 62mo, TTP was 76mo, and OS was not reached. An extensive list of pretreatment characteristics were evaluated in univariable analyses as traditional factors including age, Rai stage, beta-2 microglobulin (β2M), CD38, and others, as well as newer prognostic factors including chromosome abnormalities by FISH, IgVH MS and ZAP70 expression by immunohistochemistry. Clinical endpoints included complete remission (CR), TTP, and OS. Multiple factors were significant (p<.05) and varied according to clinical endpoint. Next, we evaluated these significant factors in multivariable (MV) analyses to identify the significant (p<.05) independent factors for each endpoint. The rank order importance for each independent factor identified in the MV model with current follow-up is shown (Table 1).
Table 1 Multivariable Model
| . | CR . | TTP . | OS . |
|---|---|---|---|
| We evaluated the newer prognostic factors (IgVH MS, del 17p, and ZAP70) separately in each final MV model to assess significant (p<.05) independent correlations (Table 2). | |||
| # Pts in Model | 483 | 301 | 483 |
| # Events | 351 | 101 | 106 |
| Characteristic | Rank-Order Significance in MV Model | ||
| β2M | 1 | - | 1 |
| Hemoglobin | 2 | - | - |
| Age | - | 2 | 2 |
| CD38 (30% cut point) | - | 3 | - |
| IgVH MS | - | 1 | - |
| . | CR . | TTP . | OS . |
|---|---|---|---|
| We evaluated the newer prognostic factors (IgVH MS, del 17p, and ZAP70) separately in each final MV model to assess significant (p<.05) independent correlations (Table 2). | |||
| # Pts in Model | 483 | 301 | 483 |
| # Events | 351 | 101 | 106 |
| Characteristic | Rank-Order Significance in MV Model | ||
| β2M | 1 | - | 1 |
| Hemoglobin | 2 | - | - |
| Age | - | 2 | 2 |
| CD38 (30% cut point) | - | 3 | - |
| IgVH MS | - | 1 | - |
Table 2 Significance of Factor in MV Model
| Characteristic . | CR . | TTP . | OS . |
|---|---|---|---|
| When including del 17p in models for TTP and OS, age and IgVH MS were no longer significant. Continued follow-up may identify additional important factors for time-toevent endpoints. Nomograms will be developed for each endpoint and full analyses will be shown. These analyses enable us to generate expectations and help in evaluating efficacy of new regimens for patients going on frontline CIT. Age, β2M, and del 17p appear to be the most important independent factors for OS in previously untreated patients who receive frontline CIT. Considering the newer prognostic factors, β2M continues to remain a major, independent, significant prognostic factor. | |||
| Del 17p | p<.05 | p<.05 | p<.05 |
| IgVH MS | Not Sig. | p<.05 | Not Sig. |
| ZAP70 | Not Sig. | p<.05 | p<.05 |
| Characteristic . | CR . | TTP . | OS . |
|---|---|---|---|
| When including del 17p in models for TTP and OS, age and IgVH MS were no longer significant. Continued follow-up may identify additional important factors for time-toevent endpoints. Nomograms will be developed for each endpoint and full analyses will be shown. These analyses enable us to generate expectations and help in evaluating efficacy of new regimens for patients going on frontline CIT. Age, β2M, and del 17p appear to be the most important independent factors for OS in previously untreated patients who receive frontline CIT. Considering the newer prognostic factors, β2M continues to remain a major, independent, significant prognostic factor. | |||
| Del 17p | p<.05 | p<.05 | p<.05 |
| IgVH MS | Not Sig. | p<.05 | Not Sig. |
| ZAP70 | Not Sig. | p<.05 | p<.05 |
Disclosures: No relevant conflicts of interest to declare.
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