Volume 16, Issue 3 , Pages 376-383, March 2010
New-Onset Lymphopenia Assessed during Routine Follow-up Is a Risk Factor for Relapse Postautologous Peripheral Blood Hematopoietic Stem Cell Transplantation in Patients with Diffuse Large B-Cell Lymphoma
Article Outline
A specific predictor during routine follow-up to ascertain risk for postautologous peripheral blood hematopoietic stem cell transplantation (post-APHSCT) relapse in non-Hodgkin lymphoma (NHL) has not been identified. Thus, we studied if new-onset lymphopenia measured by the absolute lymphocyte count (ALC) was a marker of post-APHSCT NHL relapse. ALC was obtained at the time of confirmed relapse, and at last follow-up with no relapse. From 1993 until 2005, 269 patients treated with APHSCT for diffuse large B-cell lymphoma (DLBCL) were included in this study. Patients at last follow-up without relapse (N
=137) had a higher ALC compared with those with low ALC at the time of confirmed relapsed (N=132) (median ALC ×109/L of 1.66 versus 0.71, P < .0001, respectively). ALC at follow-up was a strong predictor for relapse with an area under the curve (AUC)=0.86 (P < .0001). An ALC <1.0×109/L at the time of confirmed relapse had a positive predictive value of 89% and a positive likelihood ratio of 8.4 to predict relapse post-APHSCT. Patients with an ALC ≥1.0×109/L (N=147) had a cumulative incidence of relapse of 19% versus 92%, with an ALC <1.0×109/L (N=122) (P < .0001). This study suggests that new-onset lymphopenia measured by ALC can be used as marker to assess risk of DLBCL relapse during routine follow-up for after APHSCT.
Key Words: Absolute lymphocyte count, Autologous peripheral blood hematopoietic stem cell transplantation, Diffuse large B cell lymphoma, Relapse
Introduction
Risk factors used to assess clinical outcomes in non-Hodgkin lymphoma (NHL) patients treated with autologous peripheral blood hematopoietic stem cell transplantation (APHSCT) are identified prior to APHSCT [1]. Even though these risk factors are critical to guide transplant physicians in the selection of which patient would benefit from APHSCT, a limitation of these risk factors is that they are tested at 1 point in time. A routine risk factor or a risk factor that can be checked at any time during follow-up post-APHSCT and it retains its ability to predict relapse at any time would be a powerful tool to help transplant clinicians to identify patients who might require further treatments options post-APHSCT. In allogeneic stem cell transplantation (allo-SCT), serial chimerism analysis could be considered a routine risk factor that has shown to predict relapses after allo-SCT 2, 3, 4. In addition, high donor chimerism levels among immune cells (T cells and natural killer [NK] cells) might be a surrogate marker for graft-versus-tumor (GVT) effect [4]. Absolute lymphocyte count (ALC)-15 has been considered a surrogate marker for autologous GVT effect affecting clinical outcomes post-APHSCT 5, 6. However, in APHSCT, there has been no specific report attesting for a routine risk factor post-APHSCT. Thus, we set out to investigate if the development of new-onset lymphopenia measured by the ALC at last follow-up or at the time of confirmed relapse is a marker for relapse post-APHSCT in patients with diffuse large B cell lymphoma (DLBCL).
Methods
Patient Population
To participate in this study patients were required to have the diagnosis of DLBCL and to have undergone an APHSCT. From February 2, 1993, until December 31, 2005, 484 patients underwent autologous stem cell transplantation for NHL. Of the 484 NHL patients, 269 (56%) patients qualified for the study. Fifty-seven patients were excluded because they had bone marrow (BM) harvest; 60 patients were excluded because they had the combination of BM harvest and peripheral blood stem cells (PBSCs); and 105 patients were excluded because they had different lymphoma types than DLBCL. Data from transplant recipients were collected prospectively and entered into a computerized database. No patients were lost to follow-up. All patients gave written, informed consent allowing the use of their medical records for medical research. Approval for the retrospective review of these records was obtained from the Mayo Clinic institutional review board and was in accordance with U.S. federal regulations and the Declaration of Helsinki.
Endpoint
The primary endpoint of the study was to assess if new-onset lymphopenia measured by ALC at last follow-up or at the time of confirmed relapse is a reliable marker to predict relapse post-APHSCT.
Risk Factors for Relapse
Risk factors tested in the study included ALC at last follow-up or at the time of confirmed relapse, lactate dehydrogenase (LDH) at last follow-up, or at the time of confirmed relapse, international prognostic index (IPI) at last relapse pre-APHSCT1 (age ≥60 years, extranodal sites ≥2, LDH [abnormal versus normal levels], performance status ≥2, and stage [I/II versus III/IV]), disease status prior to APHSCT (complete response [CR] versus partial response [PR]), ALC at day 15 post-APHSCT (ALC-15≥500 cells/μ). This cutoff value for the ALC-15 was based on data from our previous studies [5], and infused CD34 stem cell count.
Conditioning Regimen
Three patients received Zevalin 0.3mCi/kg in combination with (BCNU) 300mg/m2 on day −6, etoposide 100mg/m2 twice a day on days −5, −4, −3, and −2, ARA-C 100mg/m2 twice a day on days −5, −4, −3, and −2, and melphalan (Mel) 140mg/m2 on day −1 (BEAM); 9 patients received cyclophosphamide (Cy; 60mg/m2) and total body irradiation (TBI; 12Gy); 58 patients received BCNU 300mg/m2 on day −6, etoposide 100mg/m2 twice a day on days −5, −4, −3, and −2, ARA-C 100mg/m2 twice a day on days −5, −4, −3, and −2, and Cy 35mg/kg on day −1 (BEAC); and 199 patients received BCNU 300mg/m2 on day −6, etoposide 100mg/m2 twice a day on days −5, −4, −3, and −2, ARA-C 100mg/m2 twice a day on days −5, −4, −3, and −2, and Mel 140mg/m2 on day −1 (BEAM).
Response
Response criteria were based on the guidelines by the new revised response criteria from the Lymphoma International Workshop [7]. Relapse was defined as any new lesions or increase by ≥50% of previously involved sites from nadir [7]. Time to relapse was measured from the date of transplantation to the date of relapse. Last follow-up was measured from the date of transplantation to the day of last follow-up or death in patients without any evidence of relapse.
Statistical Analysis
To assess the effect of ALC at last follow-up or at the time of confirmed relapse on relapse post-APHSCT, the relapse endpoint was examined both as cumulative incidence and cumulative hazard function plot. The cumulative incidence explicitly accounts for death from other causes besides lymphoma as competing risk and was estimated using the method of Gooley and colleagues [8]. The hazard function is the principal estimable quantity in competing risks, which can be viewed as a probability of failure specifically resulting from a cause in a small interval of time, given that no failure of any kind has occurred thus far. The cumulative hazard function Λ (t) equals the value of its corresponding hazard function summed up to time t [9]. The cumulative hazard function was calculated using the Nelson-Aalen estimator [10]. The association of ALC at last follow-up or at the time of confirmed relapse and risk factors with the incidence of relapse was also explored using logistic regression models.
The choice of optimal cutoff of ALC at last follow-up or at the time of confirmed relapse was based on its utility as a marker for relapse using box plot, receiver operating characteristics (ROC) curves, and area under the curve (AUC). χ2-tests were used to determine relationships between categoric variables. The Wilcoxon rank test was used to determine associations between continuous variables and categories, and Pearson correlation coefficients were used to evaluate associations for continuous variables. The Mahalanobis distance was used as an independent approach to assess the robustness of the Pearson correlation. All P values represented were 2 sided, and statistical significance was declared at P < .05.
Results
Patient Characteristics
The median age at the time of transplant for this cohort of 269 DLBCL patients was 56 years (range: 17-76 years). Distribution of additional baseline characteristics for these patients are presented in Table 1, and are summarized based on whether patients had an ALC <1.0×109/L versus ALC ≥1.0×109/L at last follow-up or at the time of confirmed relapse. None of the patients received purged or CD34-selected stem cells.
Table 1. Patient's Baseline Characteristics Based on ALC <1.0 versus ALC ≥1.0×109/L at Relapse or Last Follow-up
| Characteristics | ALC <1.0×109/L (N=122) | ALC ≥1.0×109/L (N=147) | P-Value |
|---|---|---|---|
| Age at transplant, years; median (range) | 56 (17-76) | 56 (19-76) | .6 |
| Sex | .5 | ||
| Female | 45 | 61 | |
| Male | 77 | 86 | |
| Prognostic factors | |||
| Extranodal sites | .5 | ||
| 0 | 89 | 100 | |
| 1 | 24 | 39 | |
| 2 | 7 | 7 | |
| 3 | 2 | 1 | |
| LDH (U/L) median (range) | 205.5 (60-2600) | 202 (110-4425) | .6 |
| Performance status | .2 | ||
| 0 | 30 | 50 | |
| 1 | 87 | 94 | |
| 2 | 5 | 3 | |
| Stage | .06 | ||
| I | 15 | 19 | |
| II | 16 | 24 | |
| III | 35 | 22 | |
| IV | 56 | 82 | |
| IPI index at last relapse pre-APHSCT | |||
| Age at transplant | .9 | ||
| ≥60 years | 44 | 54 | |
| <60 years | 78 | 93 | |
| Extranodal sites | .6 | ||
| >1 | 9 | 8 | |
| ≤1 | 113 | 139 | |
| LDH (U/L) | .7 | ||
| Normal | 67 | 85 | |
| Abnormal | 55 | 62 | |
| Performance status | .5 | ||
| ≥2 | 5 | 3 | |
| <2 | 117 | 144 | |
| Stage | .5 | ||
| I/II | 31 | 43 | |
| III/IV | 91 | 104 | |
| IPI score | .8 | ||
| 0 | 21 | 25 | |
| 1 | 35 | 53 | |
| 2 | 47 | 48 | |
| 3 | 17 | 19 | |
| 4 | 2 | 2 | |
| Number of prior treatment before APHSCT | .2 | ||
| 1 | 20 | 30 | |
| 2 | 73 | 92 | |
| 3 | 26 | 19 | |
| 4 | 3 | 3 | |
| 5 | 0 | 2 | |
| Disease status prior to APHSCT | .06 | ||
| CR | 26 | 47 | |
| PR | 96 | 100 | |
| Conditioning regimen | .1 | ||
| BEAC | 31 | 27 | |
| BEAM | 88 | 111 | |
| Zevalin+BEAM | 0 | 3 | |
| Cy/TBI | 3 | 6 | |
| Infused CD34 stem cells ×106/kg: median (range) | 3.58 (2-10.35) | 4.1 (2-14.85) | .3 |
| Post-APHSCT growth factor | .4 | ||
| G-CSF | 37 | 38 | |
| GM-CSF | 85 | 109 | |
| ALC-15 cells/μL | <.0001 | ||
| ≥500 | 45 | 106 | |
| <500 | 77 | 41 | |
| Hemoglobin at the time of confirmed relapse or last follow-up: median (range), g/dL | 12.5 (7.8-15.4) | 13.3 (7.6-16.6 | .3 |
| WBC count at the time of confirmed relapse or last follow-up: median (range) ×109/L | 5.25 (1.0-12.3) | 6.0 (1.7-12.5) | 0.6 |
| ANC at the time of confirmed relapse or last follow-up: median (range) ×109/L | 3.3 (0.67-11.52) | 3.3 (0.19-10.08) | .7 |
| Plts at the time of confirmed relapse or last follow-up: median (range) ×109/L | 165.5 (5-486) | 181 (11-462) | .1 |
| BM pre-APHSCT | .2 | ||
| Positive | 3 | 9 | |
| Negative | 119 | 138 | |
| Rituxan pre-APHSCT | 1 | 1 | .8 |
| Yes | 52 | 65 | |
| No | 70 | 82 | |
| Post-APHSCT consolidation ×RT | .8 | ||
| Yes | 15 | 20 | |
| No | 107 | 127 | |
The median follow-up on living patients in this cohort was 52 months (range: 16-122 months). One-hundred thirty-two (49%) patients had confirmed relapse post-APHSCT with a median time to relapse of 11 months (range: 3-84 months). Of the 135 (50%) patients that had died, 110 (81%) resulted from relapse of lymphoma. The day 100 treatment-related mortality (TRM) of this cohort was 5% (13/269). Of the 109 patients with an ALC <1.0×109/L obtained at the time of confirmed diagnosis, the median time of the decrease ALC, which correlates with the median time of relapse in this subgroup of patients, was 6.7 months (range: 3-47.7 months).
ALC at Last Follow-up or at the Time of Confirmed Relapse Post-APHSCT
In an attempt to identify risk factors during follow-up that influence relapse post-APHSCT, we assessed the utility of ALC at last follow-up or at the time of confirmed relapse post-APHSCT as a marker for this relevant clinical outcome. Patients without evidence of relapse (N=137) at last follow-up had a higher ALC compared with those with relapse (N=132) post-APHSCT (median ALC×109/L of 1.66 [range: 0.13-3.69] versus 0.71 [range: 0.03-4.75], P < .0001, respectively). ROC and AUC analysis showed that ALC at last follow-up or at the time of confirmed relapse was a significant marker for relapse post-APHSCT (AUC=0.86, P < .0001; Figure 1). Based on these results an ALC at last follow-up or at the time confirmed relapse of 1.0×109/L was considered optimal. Therefore, this cutoff is evaluated for ALC at last follow-up or at the time confirmed relapse in all subsequent analysis in this study.
Figure 1
ROC curve to evaluate ALC at follow-up post-APHSCT as a marker for relapse. Specifically, this curve plots the sensitivity versus 1 minus the specificity of this marker for relapse. The corresponding AUC analysis indicated that ALC at follow-up post-APHSCT was indeed a significant marker for relapse (AUC
=0.86, P < .0001).
To assess the predictive value of ALC at last follow-up or at the time of confirmed relapse as a test to predict relapse at the time of follow-up post-APHSCT, a contingency table was created between ALC ≥ versus <1.0×109/L at last follow-up or at the time of confirmed relapse status post-APHSCT (Table 2). Of the 122 patients with an ALC <1.0×109/L, 109 (89%) experienced relapse compared with 23 of 147 (16%) of patients with an ALC ≥1.0×109/L (P < .0001). The sensitivity and specificity for ALC at last follow-up or at the time of confirmed relapse was 83% and 90%, respectively. The relative risk to develop relapse with an ALC <1.0×109/L at last follow-up or at the time of confirmed relapse was 5.7 (95% confidence interval [CI]: 3.90-8.35) and an odd ratio of 45.2 (95% CI: 21.8-93.5). The positive predictive value with an ALC <1.0×109/L at last follow-up or at the time of confirmed relapse was 89% and the negative predictive value with an ALC ≥1.0×109/L at follow-up was 83%. The likelihood ratio for relapse with an ALC <1.0×109/L at last follow-up or at the time of confirmed relapse was 8.4. The crude incidence rate of relapse was 49% (132/269). The 5-year cumulative incidence rate for an ALC <1.0×109/L at last follow-up or at the time of confirmed relapse was 92%, compared with 19% for an ALC ≥1.0×109/L at last follow-up or at the time of confirmed relapse (P < .0001) (Figure 2). The 5-year cumulative hazard rate for an ALC <1.0×109/L at last follow-up or at the time of confirmed relapse was 2.4, compared with 0.2 for an ALC ≥1.0×109/L at last follow-up or at the time of confirmed relapse (P<.0001).
Table 2. Contingency Table
| Relapse at Follow-up Post-APHSCT | |||
|---|---|---|---|
| Count | Yes | No | |
| ALC <1.0×109/L at last follow-up or at the time of confirmed relapse post-APHSCT | 109 (a) | 13 (b) | 122 |
| ALC ≥1.0×109/L at last follow-up or at the time of confirmed relapse post-APHSCT | 23 (c) | 124 (d) | 147 |
| 132 | 137 | 269 | |
Figure 2
Cumulative incidence for relapse based on ALC at follow-up post APHSCT. Patients with an ALC <1.0
×109/L at follow-up experienced a higher cumulative incidence of 92% compared with a cumulative incidence of 19% for patients with an ALC ≥1.0×109/L at follow-up post-APHSCT.
Logistic regression models for predicting relapse post-APHSCT further indicate that ALC at last follow-up or at the time of confirmed relapse is significantly correlated with this clinical outcome (P < .0001). Other significant factors for relapse post-APHSCT in the univariate setting included ALC-15 (P < .0001), elevated LDH at last follow-up or at the time of confirmed relapse (P < .0001), and infused CD34 stem cells (P < .02) (Table 3). When these factors were accounted for in addition to ALC at last follow-up or at the time of confirmed relapse in a multivariate logistic regression model (Table 3), ALC at last follow-up or at the time of confirmed relapse remained a significant correlate for relapse post-APHSCT (P < .0001). An ALC <1.0×109/L at last follow-up or at the time of confirmed relapse was associated with an adjusted odds ratio for relapse post-APHSCT of 52 (95% CI: 31.8-90.1).
Table 3. Univariate and Multivariate Analysis for Relapse
| Univariate Analysis | Multivariate Analysis | |||||||
|---|---|---|---|---|---|---|---|---|
| Characteristics | Estimate | Standard Error | χ2 | P-Value | Estimate | Standard Error | χ2 | P-Value |
| Age >60 years | −0.09 | 0.13 | 0.54 | .5 | ||||
| ALC-15<500 cells/μL | −0.69 | 0.13 | 28.28 | <.0001 | −0.31 | 0.20 | 2.39 | .1 |
| ALC <1.0×109/L at last follow-up or at the time of confirmed relapse | −1.9 | 0.19 | 105.53 | <.0001 | −1.68 | 0.20 | 69.35 | <.0001 |
| LDH abnormal at last follow-up or at the time of confirmed relapse | −0.9 | 0.15 | 42.41 | <.0001 | −0.72 | 0.21 | 11.83 | <.0006 |
| CD34 | −0.1 | 0.06 | 4.8 | <.02 | −0.11 | 0.10 | 1.07 | .3 |
| Extranodal disease >1 at last relapse pre-APHSCT | −0.21 | 0.25 | 0.68 | .4 | ||||
| LDH abnormal at last relapse pre-APHSCT | −0.46 | 0.19 | 1.88 | .4 | ||||
| PS >1 at last relapse pre-APHSCT | −0.02 | 0.36 | 0.01 | .9 | ||||
| Stage III/IV at last relapse pre-APHSCT | −0.01 | 0.14 | 0.01 | .9 | ||||
| IPI >1 at last relapse pre-APHSCT | −0.14 | 0.12 | 1.34 | .2 | ||||
Confounding Factors
A major limitation of retrospective study design is the intrinsic inability of retrospective studies to control for confounding factors that could affect the outcome studied. To evaluate for any discrepancy between patients' baseline characteristics and ALC at last follow-up or at the time of confirmed relapse post-APHSCT, patients were divided into 2 groups: 1 group with ALC <1.0×109/L and another group with ALC ≥1.0×109/L at last follow-up or at the time of confirmed relapse post-APHSCT. The only statistical difference between both groups was ALC-15 (Table 1). Stage and disease status at transplant showed a statistical trend; however, in a logistic regression model, neither of them was associated with ALC at last follow-up or at the time of confirmed relapse: disease status at transplant (P=0.4) and stage (P=0.4). However, we identified a positive correlation between ALC-15 and ALC at last follow-up or at the time of confirmed relapse before (r=.34, P < .0001) and after (r=.31, P < .0001) outliers identified by the Mahalanobis distance were eliminated.
Furthermore, confounding factors that could lead to lymphopenia were assessed. None of the patients in this study were human immunodeficiency virus (HIV) positive or received post-APHSCT maintenance rituximab. There was no association between post-APHSCT consolidation radiation therapy and ALC at last follow-up or at the time of confirmed relapse ×109/L post-APHSCT (P=.8). No association was also observed between the number of prior treatments before APHSCT and ALC at last follow-up or at the time of confirmed relapse ×109/L post-APHSCT (P=.2): 1 treatment (median ALC=1.2 [range: 0.13-2.9]); 2 treatments (median ALC=1.1 [range: 0.1-4.75]); 3 treatments (median ALC=0.8 [range: 0.06-2.8]); 4 treatments (median ALC=1.0 [range: 0.25-3.2]); and 5 treatments (median ALC=1.9 [range: 1.89-2.7]). Similarly, no association was identified between the conditioning regimens and ALC at last follow-up or at the time of confirmed relapse at follow-up ×109/L post-APHSCT (P=.5): BEAC (median ALC=1.0 [range: 0.25-3.07]); BEAM (median ALC=1.1 [range: 0.06-4.75]); CTX/TBI (median ALC=1.4 [range: 0.24-2.8]); and Zevalin/BEAM (median ALC=1.6 [range: 1.0-2.5]). In addition, there was no difference between both groups (ALC≥1 versus ALC<1) regarding hemoglobin, white blood cell (WBC) count, absolute neutrophil count (ANC), and platelet count obtained at last follow-up or at the time of confirmed relapse (Table 1). No differences between both groups were also observed regarding the use of rituxan pre-APHSCT and positive BM involvement pre-APHSCT. Of the 132 patients with relapse, 12 (9%) had positive BM involvement: 2 patients with the ALC ≥1×109/L group and 10 patients in the ALC <1×109/L group at the time of confirmed relapse.
ALC and LDH at Last Follow-up or at the Time of Confirmed Relapse Post-APHSCT
LDH at last follow-up or at the time of confirmed relapse post-APHSCT in this study was also identified as a risk factor for relapse post-APHSCT. LDH is considered a surrogate marker for tumor burden in NHL. Similarly, ALC can be considered a surrogate marker of host immunity [11]. Thus, using these 2 standarized, low-cost biomarkers, we assessed if there was any correlation between tumor burden and host immunity. We identified a negative correlation between ALC and LDH at last follow-up or at the time of confirmed relapse before (r=−.34, P < .0001) and after (r=−.32, P < .0001) outliers identified by the Mahalanobis distance were eliminated (Figure 3). Because of this negative correlation and the fact that both markers are predictor of relapse when check during follow-up post-APHSCT, we assessed the cumulative incidence of relapse combining both markers. We found lower cumulative incidence of relapse in patients with a higher ALC compared with patients with low ALC regardless if the LDH was normal or abnormal at last follow-up or at the time of confirmed relapse post-APHSCT (Figure 4).
Figure 3
Scatterplot comparing ALC at follow-up and LDH at follow-up post-APHSCT. A negative correlation was identified between ALC and LDH at follow-up post-APHSCT. Arrows indicate those points that according to the Mahalanobis distances are outliers. R1 and R2 correspond to the Pearson' r values before and after eliminating possible outliers. The regression line was estimated after the elimination of outliers.
Figure 4
Cumulative incidence for relapse based on the ALC and LDH at follow-up post-APHSCT. Patients with an ALC <1.0
×109/L experienced a higher cumulative incidence of relapse regardless if the LDH was normal or abnormal at follow-up compared with a lower cumulative incidence of relapse with an ALC ≥1.0×109/L regardless if the LDH was normal or abnormal at follow-up post-APHSCT.
Discussion
The current risk factors used to assess clinical response in NHL patients treated with APHSCT are identified prior to APHSCT such as the IPI [1]. However, a limitation of these risk factors is that they are tested at 1 point in time and they are assumed to retain their predictive ability to determine clinical response at any time post-APHSCT. An ideal risk factor is a risk factor that not only has the ability to predict future clinical outcomes, but also clinical outcome at any given time point after therapy has been implemented. Therefore, we set out to investigate if ALC checked at any given time during follow-up is a marker of relapse in DLBCL patients treated with APHSCT.
Our study shows that DLBCL patients with confirmed relapse at follow-up had a lower ALC compared with those without evidence of relapse at last follow-up post-APHSCT. A low ALC at last follow-up or at the time of confirmed relapse was associated with a high odd ratio, high relative risk, high sensitivity, high positive predictive value, high cumulative hazard rate, and high cumulative incidence for relapse compared with patients with a high ALC at last follow-up or at the time of confirmed relapse that was associated with a high specificity, low negative predictive value, and low cumulative hazard rate and cumulative incidence for relapse post-APHSCT.
Within the limitations of our retrospective study, these data can only be viewed as hypothesis generating. Based our findings the association of decreased ALC and increased risk of NHL relapse (coincident with elevation of serum LDH concentrations) could be the result of either: (1) primary failure of immune surveillance yielding a permissive systemic immunologic environment allowing for clinical NHL relapse; or (2) primary NHL relapse driven by tumor-associated events, which in turn, produce mediators of immune suppression manifesting as a decrease in ALC. Our current data is unable to distinguish between these 2 possibilities. However, to the extent that ALC can be viewed as a surrogate marker of immune competence, there are numerous examples in which the presence of competent systemic immunity directly impacts NHL biology. Possibly the best clinical example in support of this notion is the natural history of posttransplant lymphoproliferative disorders (PTLD). In this context, a frequently effective therapeutic intervention against the NHL is a simple reduction of immunosuppression, currently employed as “standard of care.” An associated, albeit less profound clinical observation is the association of ALC and efficacy of rituximab therapy in patients with low grade NHL [12]. Patients with normal ALC have a significantly higher likelihood of good clinical outcomes following rituximab therapy relative to those with low ALC. Assuming that 1 aspect of effective rituximab therapy is its ability to mediate antibody-dependent cellular cytotoxicity (ADCC), presence of competent immunity (reflected by normal ALC) appears critical to clinical outcomes. However, despite these associations, a mechanistic explanation for the increased risk for NHL in patients that demonstrate low ALC can only be addressed in an appropriately designed prospective clinical trial where relevant analyses of both systemic immunity and tumor phenotype can be studied. Such an endeavor is currently under way. Nevertheless, based on the presented data, the association between ALC and NHL relapse seems clinically useful in judging risk for NHL relapse in patients in clinical follow-up post-APHSCT.
To minimize the inherited biases of a retrospective study the following steps were taken. First, we selected only patients that had their stem cell collected through the PB as PBSC collection is considered the preferred mode of stem cell collection for autologous SCT with lower side effects and faster engraftment compared with stem cells collected by BM harvest [13]. Second, we selected patients with DLBCL because DLBCL is the most common lymphoma type for which APHSCT is indicated as the standard of care for patients that failed initial therapy [14]. Another reason to only select DLBCL patients was to have a homogenous group of patients. The authors of this study are well aware that within DLBCL, 3 biologically distinct categories of DLBCL have been described based on gene expression profiling including germinal center B cell-like (GCB), activated B cell-like, and type 3, with a predominant T cell signature [15]. Patients with GCB derived DLBCL have a higher chance of cure than non-GCB patients when treated with conventional anthracycline based chemotherapy [16]. However, our group recently published similar clinical outcome with GCB DLBCL patients and non-GCB DLBCL patients treated with autologous SCT, suggesting that the use of intensified therapy may overcome the negative impact of the non-GCB phenotype [17]. Third, we could not identify any medications or infections that could have affected the ALC at follow-up. Fourth, outside from ALC-15, all the baseline patients' characteristics were balanced between the ALC ≥ versus <1.0×109/L groups, including specifically the number of prior treatments before APHSCT, as well as none of the patients received Flu-based therapy.
On the other hand, the strength of this study included the analysis of a large cohort of patients, with enough follow-up to attest for the use of ALC at follow-up post-APHSCT as a marker for relapse. Second, the study identified a worldwide, standarized, low-cost risk factor in the ALC at follow-up to assess relapse post-APHSCT. Third, to our knowledge, this study identified for the first time ALC at follow-up as a marker to assess relapse at any given point in time during follow-up post-APHSCT in DLBCL. Thus, our study suggests that the ALC at follow-up can be used as a simple, inexpensive tool to alert transplant clinicians of relapse during follow-up post-APHSCT in DLBCL
Financial disclosure: The authors have nothing to disclose.
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Financial disclosure: See Acknowledgments on page 382.
PII: S1083-8791(09)00510-2
doi:10.1016/j.bbmt.2009.10.029
© 2010 American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.
Volume 16, Issue 3 , Pages 376-383, March 2010
