Hypogammaglobulinemia Following Rituximab and High-Dose Therapy and Autologous Stem-Cell Transplant: Incidence and Predictors of Prolonged Immunoglobulin Deficiencies
Bibliographic record
Abstract
Abstract High-dose therapy and autologous stem cell transplantation (HDT/ASCT) and rituximab immunotherapy have been increasingly applied in the management of non-Hodgkin’s lymphomas (NHL). Although both approaches have been individually associated with B-cell depletion and hypogammaglobulinemia, the incidence, time course, and predictors of prolonged deficiencies following a combined treatment approach is unknown. Methods: We completed a series of prospective phase II studies of HDT/ASCT combined with rituximab for patients with relapsed follicular lymphoma (FL) or diffuse large B cell lymphoma (DLBCL). In two phase II trials of patients with FL (R/Tx and R-IFN/Tx), patients received 9 infusions of rituximab 375mg/m2 as both an in vivo purge and as maintenance post HDT/ASCT. In a trial with relapsed DLBCL or transformed lymphoma, patients received 8 infusions with rituximab 375mg/m2 only as part of the salvage chemotherapy regimen (R-ESHAP/Tx). Immunoglobulin levels were expressed as percentages with 100% representing the lower limit of normal at the institutional lab. Hypogammaglobulinemia was defined as <75% of this lower limit. A time-to-recovery from hypogammaglobulinemia was determined by Kaplan-Meier statistics. Results: Fifty-one patients with FL were transplanted and were subsequently treated with maintenance rituximab (R/Tx study) or with maintenance rituximab (MR) and interferon-alpha (R-IFN/Tx). Twenty-six patients with relapsed aggressive-histology lymphoma were transplanted with the R-ESHAP salvage regimen. The mean age of the FL patients was 45 and the mean age of the aggressive-histology lymphoma patients was 49. The median number of prior therapies was 1 (range 1–3) for the FL patients and bone marrow involvement at study entry was present in 63%. The median number of prior therapies was 1 (range 1–5) for the aggressive-histology lymphoma patients and bone marrow involvement was present in 15%. Baseline IgG hypogammaglobulinemia was seen in 18% of patients with relapsed FL and 15% of patients with relapsed DLBCL/transformed lymphoma. Median baseline Ig levels in each study are displayed in Figure 1. Patients with FL undergoing HDT/ASCT and MR (combined R/Tx and R-IFN/Tx studies) had prolonged IgG hypogammaglobulinemia compared to patients with aggressive-histology lymphoma (log-rank p=0.0047; see Figure 2). The median time-to-recovery from hypogammaglobulinemia had not been reached after a median follow-up of 42 months. Similarly, IgM level recovery was delayed in the FL group compared to the aggressive-histology patients (p=.0001), although late recovery was noted for this Ig subtype (median time-to-recovery 36 months post-ASCT). Univariate analyses revealed that persistent hypogammaglobulinemia (at 24 months) was associated with FL histology (vs. DLBCL/transformed; p=0.006), bone marrow involvement at study entry (p=0.008), and hypogammaglobulinemia at study entry (p=0.026). Factors not associated with persistent hypogammaglobulinemia included: number of prior therapies, age, and administration of maintenance interferon-alpha. Post-transplant (>3 months) infections included herpes zoster reactivation (n=7) and pneumonia (n=8). One individual in the R-ESHAP/Tx study died of PCP pneumonia 4 months post HDT/ASCT. A relationship between grade III-IV infections and prolonged hypogammaglobulinemia was not evident on univariate analysis (data not shown). Conclusions: Patients with follicular lymphoma undergoing high dose therapy and stem cell transplantation together with rituximab maintenance are likely to experience a prolonged hypogammaglobulinemia whereas this is less likely with patients with aggressive-histology lymphoma undergoing similar doses of rituximab as part of their salvage therapy. Further research is required to elucidate the relative contributions of disease histology, bone marrow involvement, baseline hypogammaglobulinemia, timing of rituximab infusions or other factors not yet identified. Figure Figure Figure Figure
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".