1 Swiss Group for Clinical Cancer Research (SAKK), Bern, Switzerland; 2 Istituto Europeo di Oncologia, Milano, Italy; 3 Centre Hospitalier Lyon-Sud, Lyon, France
* Correspondence to: Dr M. Ghielmini, Oncology Institute of Southern Switzerland, Ospedale San Giovanni 6500 Bellinzona. Tel: +41-91-811-79-15; Fax +41-91-811-79-16; E-mail: mghielmini{at}ticino.com
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Abstract |
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Patients and methods: Three hundred and six patients with follicular or mantle cell lymphoma received four weekly doses of rituximab (induction) and no further treatment (arm A) or four more doses at 2-month intervals (arm B).
Results: Response rate to induction was 44%. Independent predictive factors for response were disease bulk <5 cm, follicular histology, normal hemoglobin and low lymphocyte count. Factors associated with event-free survival (EFS) were having responded to induction, having received not more than one line of therapy, Ann Arbor stage IIII, high lymphocyte count, disease bulk <5 cm, Fc-gamma receptor genotype VV and receiving prolonged treatment. B cells were suppressed by treatment but recovered after a median of 12 months in arm A and 18 months in arm B. The median IgM level after 1 year was normal in arm A but was decreased to 73% of baseline in arm B. We observed 24 serious adverse events, equally distributed between arms. Ten patients receiving induction only and six patients receiving prolonged treatment developed a second tumor.
Conclusions: We defined the characteristics predicting response and EFS to rituximab. Prolonged treatment results in longer EFS at the cost of a longer reduction in B cell and IgM levels, but without additional clinical toxicity.
Key words:
rituximab, predictive factors, toxicity, Fc- receptor, follicular lymphoma, mantle cell lymphoma
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Introduction |
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Single agent rituximab is one of these options, having been shown to cause little toxicity and to obtain, given at a prolonged schedule and in some patient subsets, remissions that are comparable to what is obtained with multi-agent regimens [5, 6
]. However, many are still reluctant in applying single-agent immunotherapy, fearing an insufficient activity compared with other more traditional schemes.
The efficacy of antibody treatment was shown to differ among lymphoma subtypes, but the reason why some histologies respond better than others has not been clarified. Due to the different mechanisms of action of monoclonal antibodies, it is possible that some mechanisms are more effective against some tumor types than against others, but it could as well be that certain histologies are more associated with biological or clinical characteristics of the patient that influence treatment response. Furthermore, a prospective and prolonged observation of relevant clinical and immunological side-effects in a large cohort of patients treated with the single agent has not been reported.
We therefore analyzed an important number of characteristics of 306 patients with FL or MCL and of their disease that could predict benefit from treatment with single-agent rituximab, based on data of the SAKK trial 35/98. We also describe the observed short and long-term major side-effects. This exploratory analysis intended to identify potential factors that are associated with response, event-free survival (EFS) and toxicity.
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Patients and methods |
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Patients were initially treated with rituximab 375 mg/m2 per week for 4 weeks (induction phase). Patients with stable disease or in partial or complete response at week 12 (from treatment start) were randomized in a 1:1 ratio into two groups: no further treatment (arm A, standard treatment) or treatment with a single infusion of rituximab 375 mg/m2 at week 12, and again at months 5, 7 and 9 (arm B, prolonged treatment). The randomization was stratified according to status of disease at trial entry (first presentation versus refractory or relapsed), response to induction treatment (stable disease versus response) and center. Patients were centrally randomized by the minimization method via fax at the SAKK Coordinating Center in Bern. Upon disease progression or relapse, further treatment was at the treating physician's discretion.
EFS time was the primary end point and calculated as the time from first induction infusion to progression, relapse, second tumor or death from any cause. For the randomized phase of the two subtrials, a group sequential design with two interim analyses and one final analysis was adopted. Both subtrials reached the final stage.
Patients
Inclusion criteria were a biopsy-proven follicular or mantle cell lymphoma, age 18 years and measurable disease defined as the presence of at least one previously unirradiated lesion with two measurable perpendicular diameters of which at least one should be of 2 cm. The interval between the last systemic anticancer treatment and trial entry should not be less than 28 days. Other inclusion criteria were an Eastern Cooperative Oncology Group (ECOG) performance status
2 and, after observing unexpected cardiac events in the first 10 months of the trial [7
], a cardiac ejection fraction (EF)
50% by echocardiography. Exclusion criteria included symptomatic central nervous system (CNS) disease, a history of significant medical conditions, including previous malignancies within 5 years, a reduced renal function (creatinine >2x the upper limit of normal [ULN]) or liver function (bilirubin >2x ULN). Pregnant or lactating females, patients with active opportunistic infections or patients with known HIV, hepatitis B or C infections were also excluded. Previous treatment with rituximab was not allowed. A central histology review was performed for all cases before randomization.
Trial assessments
The detailed examinations required by the trials are described elsewhere [5, 6
]. Briefly, patients underwent a complete staging at trial entry, which was repeated at 12 weeks, and at 7, 12, 18 and 24 months, then yearly or when clinically required. Re-evaluation of the bone marrow (BM) was required only at week 12 and month 12 if involved at trial entry. Routine blood counts and chemistries were assessed at baseline, before each rituximab administration and at months 2, 3, 5, 7, 9 and 12. Serum immunoglobulins (IgG, IgA, IgM) were measured at baseline and again at months 3, 7 and 12, while blood samples for immunophenotyping were taken at baseline, week 12 and months 9, 12, 18 and 24. Analysis of lymphocyte subsets was performed as described before [5
].
Statistical methods
To identify factors predictive of response to rituximab induction and EFS, we first performed preliminary univariate analyses (logistic regression for response and Cox regression for EFS) on the factors listed in Table 1. For EFS (only randomized patients were considered), further models including an additional covariate for treatment arm, with or without treatment-factor interaction, were also explored as suggested in [8]. We then selected among the factors and interactions via a stepwise procedure with entry criterion P value = 0.1 and stay criterion P value = 0.05. Finally we refit the models using data from all patients seen with non-missing values for the selected variables. Due to correlations between some variables (e.g. disease bulk at baseline and disease bulk at randomization) and numerous missing values, some factors were excluded prior to the selection procedure in order to increase model stability. The pre and post differences of lymphocyte subset counts were analyzed by the Wilcoxon signed rank test. The between-arm differences of immunoglobulin levels were compared by the Wilcoxon rank sum test. No adjustment for multiple testing was performed, therefore the reported P values should be interpreted with caution.
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Results |
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Of the 273 eligible and evaluable patients, 61 were not randomized to the second phase of the study because of disease progression or major toxicity during the induction phase.
Predictive factors for response
The response rate to rituximab induction in the 273 eligible and evaluable cases was 44% (38% partial response and 6% complete response). Among 33 factors assessed, 15 were found potentially predictive for response (Table 1). The favorable factors finally selected by the stepwise procedure were disease bulk <5 cm, follicular histology, normal hemoglobin and low blood lymphocyte count (CTC toxicity grade >1), all determined at treatment start (Table 2).
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Infections and second tumors
In the 306 patients treated, serious adverse events possibly or probably related to rituximab treatment were 13 infections, six cardiac events and five intestinal complications, resulting in seven deaths (four cardiac, two infectious, one intestinal). Further 11 serious adverse events were all non-fatal and of various nature (infusion reaction, cytopenias, renal, neurologic, metabolic). The incidence of these reactions was similar in arms A and B.
Of the 306 patients treated, 47 developed an infection: 27 during the induction phase and 20 during the post-randomization phase (eight in arm A and 12 in arm B). Of these 20 infections seven were severe (life-threatening or requiring hospitalization): two in arm A (pneumonia and candida stomatitis) and five in arm B (two pneumonia, one viral hepatitis, one cholecystitis and one severe paradontosis). The recovery of B cells and IgM tended to be slower in patients who experienced an infection compared with patients without infections (difference not significant).
There were 16 cases of second tumor (five MDS/AML and 11 solid tumours): 10/202 in patients receiving induction only, 6 of 104 in patients receiving prolonged treatment.
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Discussion |
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Some of our predictive factors are common predictive factors in all cancer patients undergoing chemotherapy: parameters associated with the amount of disease (stage and disease bulk), with the impact of the disease on patient homeostasis (hemoglobin level) or with the extent of previous treatment (number of previous therapy regimens). The lower chance of response in MCL patients compared with FL patients also reflects what is known for chemotherapy in general, and the observation that responders do better than non-responders is common as well.
Compared with other studies of single-agent rituximab, including enough cases to allow a multivariate analysis, we confirm the favorable role of FL histology for response as in the study by McLaughlin [9]. Parameters describing previous treatment history or disease extension were also found to have predictive influence by others, although the significant descriptive parameters were not the same as in our analysis [9
, 10
].
Other results from our study are more puzzling. First, it seems surprising that factors influencing response and factors affecting EFS are not the same. For instance, lymphomas with follicular histology have a higher chance of responding to rituximab, but histology was not included in the selected multivariate model for EFS. Possible explanations are: (1) different patient setsmore patients were included for response analyses than for EFS analyses (limited to randomized patients who did not progress under induction treatment); (2) confounding effectsince histology plays an important role on response to induction treatment, its impact on EFS might be partially confounded by the effect of response to induction treatment that was selected in the multivariate EFS model; (3) selection procedureapplying different selection procedures might result in different models, hence the models presented in this report should not be considered as 100% definitive. Overall, the fact that histology was not selected in the EFS model does not mean that it does not exert influence on EFS. One piece of evidence is that histology was selected in the prediction score model in which non-randomized patients were also included.
On the other hand, patient's genotype for the Fc- III receptor influences EFS (only in FL) but not the chance of responding. Finally, a lower baseline lymphocyte count predicts response, but a higher lymphocyte count after induction is associated with better EFS. Analogy to the three explanations above could also be applied here. In addition, a tentative biological explanation for these apparent contradictions could be that of the several mechanisms of action of rituximab, one (activation of the complement) is predominant during the induction phase and another one (the more lymphocyte- and Fc-
dependent ADCC [antibody dependent cell cytotoxicity]) is more active during the observation/prolonged phase. If this was true, the failure of prolonged rituximab to extend EFS in MCL [6
] could be attributed to the lack of Fc-
mediated ADCC, as our data suggests that Fc-
genotype is not a predictive factor in MCL. The observation that the effect of rituximab is Fc-
dependent in some lymphomas (as FL or lymphoplasmocytic) and not in others (as MCL or chronic lymphocitic leukemia, CLL) was made by other authors as well [11
13
].
Our data also exhibited a relatively long immunosuppression caused by the prolonged schedule of rituximab, but not associated with an increase of clinically relevant immunosuppression-associated pathologies as infections or second tumors.
In conclusion, for patients with follicular lymphoma and not suitable for an aggressive treatment, single-agent rituximab is confirmed to be a valid option, particularly if patients present with a low tumor load and normal blood counts. In these cases prolonged treatment results in significantly longer EFS. Some of these patients may, in some centres, be managed by a watch and wait policy, and studies are ongoing comparing these two strategies in this favorable population.
Even though the extended schedule causes a more prolonged reduction of B cell and IgM levels, no additional toxicity is seen. Because the response rate to rituximab is not dependent on the presence of lymphocytes and on Fc- receptor genotype, while on the other hand EFS is dependent on them, we raise the hypothesis that the mechanism of action of rituximab may differ during treatment: cytotoxic cell-independent during the early phase and cytotoxic cell-dependent during the later phase.
Received for publication June 9, 2005. Accepted for publication June 10, 2005.
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References |
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