Abstract
Abstract 2889
Poster Board II-865
Serum free light chain analysis (sFLCA) is a tool to monitor myeloma disease activity and treatment response, and stratify myeloma pts. to defined risk groups and has been incorporated into diagnostic guidelines[1]. Either the ratio of the free kappa/lambda light chains (FLCQ), the absolute value of the involved light chain (FLCi) or the difference of involved and uninvolved light chain (FLCD) may be used. While sFLCA is recommended , urine analysis (uFLCA) at the moment is not. To analyze whether results from sFLCA and uFLCA would potentially have translated into altered clinical decision making and timing of treatments compared to classical paraprotein measurements (sPPM) in a cohort of myeloma patients we analyzed all measurements routinely performed at Innsbruck University Hospital between MAR 03 and OKT 08 and correlated them to individual pts. clinical courses.
187 pts. (109 m, 78 f) out 235 pts. identified were deemed eligible. Myeloma subtypes were IgG (57.2%), IgA (21,9%), light chain only (13.9%), IgM (3.2%), oligo and nonsecretory (2.6 %, incl. 2 pts. completely asecretory), and IgD (1,0%). 4 pts. were complete immunoglobulin only secreters. According to mSMART 15% were high risk, 61% standard risk and 23,5% of unknown category. In this cohort 3202 sFLCa, 1136 uFLCa and 2583 sPPM were performed (range 2-89, median 12). This measurements were correlated with 167 treatment lines applied in this pts. (49 auto-transplants, 3 allo-transplants, 7 auto/allo procedures, 68 regimes containing novel agents and 40 conventional chemotherapeutic approaches.
Patients, Assays and Treatment Lines: 187 pts. (109 m, 78 f) out 235 pts. identified were deemed eligible. Myeloma subtypes were IgG (57.2%), IgA (21,9%), light chain only (13.9%), IgM (3.2%), oligo and nonsecretory (2.6 %, incl. 2 pts. completely asecretory), and IgD (1,0%). 4 pts. were complete immunoglobulin only secreters. According to mSMART 15% were high risk, 61% standard risk and 23,5% of unknown category. In this cohort 3202 sFLCa, 1136 uFLCa and 2583 sPPM were performed (range 2-89, median 12). This measurements were correlated with 167 treatment lines applied in this pts. (49 auto-transplants, 3 allo-transplants, 7 auto/allo procedures, 68 regimes containing novel agents and 40 conventional chemotherapeutic approaches.
sFLCa showed a significant advantage in detecting any of the predefined clinical endpoints (Table 1) . By using sPPM only , ∼ 40% of events would have been missed during the observation period. A median of 13% of the applied therapies proven to be ineffective could have been stopped and altered earlier on using the results of sFLCa.
While the use of sFLCi and sFLCD resulted in comparable rates of false pos. and neg. results (Table 2) in comparison to sPPM, sFLCQ is more sensitive to effects of immunoparesis, changes of the uninvolved FLC concentration and renal function resulting in both more false pos., as well as false neg. results. sFLCa detected relapses with a median of 3 months prior to sPPM, therapeutic effectiveness with a median of 2 therapy cycles earlier than sPPM and therapeutic failure with a median of 1 antecedent cycle of therapy. Data on uFLCa will be provided at ASH.
EVENT . | sFLCi . | sFLCQ . | sFLCD . | sPPM . | p (vs sPPM) . |
---|---|---|---|---|---|
ANTECEDENT RELAPSE | 51 | 53 | 54 | 36 | 0.1 |
ANTECEDENT REMISSION | 43 | 46 | 48 | 40 | 0.1 |
ANTECEDENT THERAPY EFFECTIVENESS | 31 | 33 | 34 | 11 | 0.1 |
ANTECEDENT THERAPY FAILURE | 18 | 15 | 16 | 4 | 0.1 |
COMBINED CLINICAL ENDPOINT (total number 154) | 143 | 147 | 152 | 91 | 0.01 |
% Detected | 92.9 | 95.4 | 98.7 | 59.1 | 0.01 |
EVENT . | sFLCi . | sFLCQ . | sFLCD . | sPPM . | p (vs sPPM) . |
---|---|---|---|---|---|
ANTECEDENT RELAPSE | 51 | 53 | 54 | 36 | 0.1 |
ANTECEDENT REMISSION | 43 | 46 | 48 | 40 | 0.1 |
ANTECEDENT THERAPY EFFECTIVENESS | 31 | 33 | 34 | 11 | 0.1 |
ANTECEDENT THERAPY FAILURE | 18 | 15 | 16 | 4 | 0.1 |
COMBINED CLINICAL ENDPOINT (total number 154) | 143 | 147 | 152 | 91 | 0.01 |
% Detected | 92.9 | 95.4 | 98.7 | 59.1 | 0.01 |
RESULTS . | sFLCi . | sFLCQ . | sFLCD . | sPPM . |
---|---|---|---|---|
FALSE POS. RELAPSE/EFFECTIVENESS PREDICTION | 1 | 8 | 1 | 0 |
FALSE NEG. RELAPSE/EFFECTIVENESS PREDICTION | 1 | 5 | 1 | 2 |
FALSE POS. REMISSION PREDICTION | 0 | 1 | 0 | 0 |
FALSE NEG. REMISSION PREDICTION | 1 | 0 | 1 | 3 |
TOTAL | 3 | 14 | 3 | 5 |
RESULTS . | sFLCi . | sFLCQ . | sFLCD . | sPPM . |
---|---|---|---|---|
FALSE POS. RELAPSE/EFFECTIVENESS PREDICTION | 1 | 8 | 1 | 0 |
FALSE NEG. RELAPSE/EFFECTIVENESS PREDICTION | 1 | 5 | 1 | 2 |
FALSE POS. REMISSION PREDICTION | 0 | 1 | 0 | 0 |
FALSE NEG. REMISSION PREDICTION | 1 | 0 | 1 | 3 |
TOTAL | 3 | 14 | 3 | 5 |
This analysis proves sFLCa to be a useful tool in monitoring myeloma pts. clinical courses and the therapeutic effectiveness of myeloma treatment approaches, even in the setting of “real life medicine”. For monitoring purposes sFLCi and sFLCD should be used preferably due the higher false pos./neg. potential of sFLCQ . By using sFLCa in a structured diagnostic pathway treatment effectiveness could be judged earlier on and altered if necessary. Thus this analysis shows a potentially clinically significant benefit to myeloma pts.
[1] Dispenzieri et al. Leukemia advance online publication 20 November 2008; doi:10.1038/leu.2008.307
No relevant conflicts of interest to declare.
Author notes
Asterisk with author names denotes non-ASH members.