Literature DB >> 29784907

A predictive model for risk of early grade ≥ 3 infection in patients with multiple myeloma not eligible for transplant: analysis of the FIRST trial.

Charles Dumontet1, Cyrille Hulin2, Meletios A Dimopoulos3, Andrew Belch4, Angela Dispenzieri5, Heinz Ludwig6, Philippe Rodon7, Jan Van Droogenbroeck8, Lugui Qiu9, Michele Cavo10, Ann Van de Velde11, Juan José Lahuerta12, Olivier Allangba13, Jae Hoon Lee14, Eileen Boyle15, Aurore Perrot16, Philippe Moreau17, Salomon Manier15, Michel Attal18, Murielle Roussel19, Mohamad Mohty20, Jean Yves Mary21, Alexandre Civet22, Bruno Costa23, Antoine Tinel23, Yann Gaston-Mathé24, Thierry Facon25.   

Abstract

Infections are a major cause of death in patients with multiple myeloma. A post hoc analysis of the phase 3 FIRST trial was conducted to characterize treatment-emergent (TE) infections and study risk factors for TE grade ≥ 3 infection. The number of TE infections/month was highest during the first 4 months of treatment (defined as early infection). Of 1613 treated patients, 340 (21.1%) experienced TE grade ≥ 3 infections in the first 18 months and 56.2% of these patients experienced their first grade ≥ 3 infection in the first 4 months. Risk of early infection was similar regardless of treatment. Based on the analyses of data in 1378 patients through multivariate logistic regression, a predictive model of first TE grade ≥ 3 infection in the first 4 months retained Eastern Cooperative Oncology Group performance status and serum β2-microglobulin, lactate dehydrogenase, and hemoglobin levels to define high- and low-risk groups showing significantly different rates of infection (24.0% vs. 7.0%, respectively; P < 0.0001). The predictive model was validated with data from three clinical trials. This predictive model of early TE grade ≥ 3 infection may be applied in the clinical setting to guide infection monitoring and strategies for infection prevention.

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Year:  2018        PMID: 29784907      PMCID: PMC5990520          DOI: 10.1038/s41375-018-0133-x

Source DB:  PubMed          Journal:  Leukemia        ISSN: 0887-6924            Impact factor:   11.528


Introduction

Patients with multiple myeloma (MM) are more susceptible to infections due to advanced age, immunodeficiency caused by the underlying disease, comorbidities, and treatment toxicities [1]. Infections are a major cause of death, particularly early death, in patients with MM, highlighting the need for preventive or early treatment measures [2-6]. A scoring system can help identify patients at risk for infections during MM treatment, enabling implementation of risk-adapted strategies to prevent early infections. To identify infection risk factors, we used data from the pivotal, phase 3 FIRST trial, which compared the efficacy and safety of lenalidomide plus low-dose dexamethasone (Rd) until disease progression (Rd continuous) vs. Rd for 18 cycles (Rd18) or melphalan, prednisone, and thalidomide (MPT) in transplant-ineligible patients with newly diagnosed MM (NDMM) [7, 8]. In this post hoc analysis, a detailed characterization of infections in the FIRST trial was conducted and prognostic factors of early treatment-emergent (TE) grade ≥ 3 infections were identified. The results were used to develop a predictive model to assess the risk of this event in patients receiving standard nonintensive treatment.

Methods

Study design

The FIRST study (MM-020/IFM07-01; NCT00689936) has been previously reported [7]. The protocol was approved by the appropriate institutional review board or independent ethics committee before study initiation. Briefly, the multinational, open-label, randomized, phase 3 trial compared the efficacy and safety of Rd continuous vs. MPT or Rd18 in transplant-ineligible patients with NDMM. Infection prophylaxis was not mandatory in the protocol.

Patients and assessments

Of the 1623 patients in the intent-to-treat population, TE infections were investigated in 1613 patients who received ≥ 1 treatment dose (safety population), including 532, 540, and 541 in the Rd continuous, Rd18, and MPT arms, respectively. TE infections were defined as infections occurring or worsening on or after the first dose of any study drug and up to 28 days after treatment discontinuation. Infections were identified by the investigator, classified per Medical Dictionary for Regulatory Activities and graded per Common Terminology Criteria for Adverse Events v3.0. Early infection was defined as occurring during the first 4 months of treatment. For comparison of the risk of infections between treatment arms, data from the Rd continuous and Rd18 arms were pooled (Rd pooled) and a χ2 test was used. Patients in the Rd18 and Rd continuous arms received the same treatment in the first 18 months, thereby supporting the pooling of data from these two arms for the investigation of infections in the first 4 or 18 months. Demographics, medical history, and baseline characteristics were analyzed to identify risk factors of early TE grade ≥ 3 infection. Of 1613 treated patients, this analysis was conducted on 1378 patients (prognostic analysis population), which excluded patients who progressed, died, or discontinued treatment and had no TE grade ≥ 3 infections in the first 4 months. External validation of the results was conducted in three independent data sets: MM-003 (NCT01311687) [9], MM-009 (NCT00056160)/MM-010 (NCT00424047) [10-12], and MM-015 (NCT00405756) [13], with 237, 444, and 391 treated patients, respectively. These trials are described in the Supplement (External Validation Trials). The numbers of patients in the various study populations in MM-020 and the validation sets are described in Supplemental Table 1.

Analysis of the impact of first TE grade ≥ 3 infection in the first 4 months on overall survival

A time-dependent Cox model analysis was performed to assess the impact of first TE grade ≥ 3 infection in the first 4 months on patient overall survival (OS) [14]. A multivariate analysis was conducted with all baseline prognostic factors identified in the study with the Q-Finder algorithm as described in the Supplement to assess the significance of the occurrence of first TE grade ≥ 3 infection in the first 4 months on OS, independent of the role of potential confounding factors. Results were expressed using the hazard ratio (HR) of death and its 95% CI.

Development and validation of first TE grade ≥ 3 infection in the first 4 months risk model

Overall, 853 variables were included in an analysis to identify rules that can predict the occurrence of the first TE grade ≥ 3 infection in the first 4 months, using the Q-Finder subgroup discovery algorithm. A rule is 1 or a combination of a few variable modalities defining a group with a high or low proportion of early TE grade ≥ 3 infection. Rules were selected based on their P-value computed with the hypergeometric law. The statistical significance cutoff for retaining rules was determined at P < 5.10 × 10−5 to adjust for multiple testing. Twenty-five rules meeting the statistical significance threshold were retained for expert review. Additional details regarding this algorithm are provided in the Supplement (Q-Finder). Upon clinical experts’ request, the cutoff value from statistically significant rules was rounded to make it easier to use, and additional tests were performed on variables with clinical significance. Statistically significant rules were selected by expert assessment based on their clinical and/or biological relevance to be included in a stepwise Akaike information criterion multivariate logistic regression model followed by an iterative variable selection process to remove variables with P ≥ 0.1 [15]. Patients with missing data on ≥ 1 input variable were excluded from the model (n = 9). The final model included six variables. A scoring system was developed by allocating points to factors of low (−1 or −2 points) or high risk (1 or 2 points) based on their coefficient in the multivariate logistic model. The cumulative score classified patients into high (2 to 5 points) or low (−3 to 1 points) infection risk groups. The concordance index (C-index), relative risk (RR) and its 95% CI, and number needed to treat (NNT) were determined. Assuming that a prevention treatment can reduce the risk of early TE grade ≥ 3 infection in 50% of the patients of the high-risk group, NNT is the number of patients in the high-risk group who had to receive the prevention treatment to avoid the occurrence of 1 early TE grade ≥ 3 infection. Thus, a higher NNT denotes a smaller benefit of the treatment. A χ2 test was used to compare the proportions of patients with ≥ 1 early TE grade ≥ 3 infection in the high- vs. low-risk groups. The model was tested on three independent validation data sets, and all metrics (C-index, RR, and NNT) were computed to evaluate the model. As a confirmatory analysis (in the MM-020 and validation sets), time to first infection was estimated in the safety population using the Kaplan–Meier method in the high- and low-risk groups and the log-rank test to assess statistical significance of the difference. In addition, a competing risk analysis with progression or death without infection and infection as competing events was performed to confirm the difference in risk of first TE grade ≥ 3 infection in the first 4 months between high- and low-risk groups in the prognostic analysis population (Supplement: Competing Risk Model) [16].

Results

Characterization of infections

Demographic and baseline characteristics of the safety population in MM-020 are presented globally and per treatment group in Supplemental Table 2. History of infections before enrollment was similar across treatments (Rd pooled: 27.2%; MPT: 28.5%). During the study, anti-infective drugs were prescribed to 78.5% and 67.1% of patients in the Rd pooled and MPT groups, respectively. Among the three treatment arms, 3125 infections of any grade occurred during the study; 3031 infections were TE (1.9 TE infection events per patient). Of 3031 TE infection events of any grade that occurred during the study in 1104 patients, 610 in 321 patients were grade ≥ 3 (representing 20.2% of 3025 TE infection events of known grade) (Table 1).
Table 1

TE infection events by grade and treatment arm in the safety population of the FIRST trial (1613 patients, including 532, 540, and 541 in the Rd continuous, Rd18, and MPT arms, respectively)

TE infection events, naGrade 1 (mild) infectionsGrade 2 (moderate) infectionsGrade 3 (severe) infectionsGrade 4 (life-threatening) infectionsGrade 5 (death) infectionsUnknown grade infections
Rd contRd18MPTTotalRd contRd18MPTTotalRd contRd18MPTTotalRd contRd18MPTTotalRd contRd18MPTTotalRd contRd18MPTTotal
Events in the first 4 months134136853551571701144415768621871716154811109300303
Events in the first 18 months339356190885440422307116914814510539835272486202015550325
Events beyond 18 months1754418317431178621063600620021001
Total5143601941068614425308134721014610546141272492222015571326

MPT melphalan, prednisone, and thalidomide, Rd cont lenalidomide plus low-dose dexamethasone until disease progression, Rd18 lenalidomide plus low-dose dexamethasone for 18 cycles, TE treatment emergent

aA total of 79 infections occurred before the first treatment administration, and 15 infections occurred > 28 days after treatment discontinuation

TE infection events by grade and treatment arm in the safety population of the FIRST trial (1613 patients, including 532, 540, and 541 in the Rd continuous, Rd18, and MPT arms, respectively) MPT melphalan, prednisone, and thalidomide, Rd cont lenalidomide plus low-dose dexamethasone until disease progression, Rd18 lenalidomide plus low-dose dexamethasone for 18 cycles, TE treatment emergent aA total of 79 infections occurred before the first treatment administration, and 15 infections occurred > 28 days after treatment discontinuation During the first 18 months of treatment, 1055 patients (65.4%) and 340 patients (21.1%) experienced TE infections of any grade and TE grade ≥ 3 infections, respectively. The risk of TE infection of any grade in the first 18 months was 69.4% with Rd pooled and 57.5% with MPT (P < 0.0001). The risk of having ≥ 1 TE grade ≥ 3 infection during the first 18 months was 22.6% (120 patients) with Rd continuous, 22.6% (122 patients) with Rd18, and 18.1% (98 patients) with MPT (Rd pooled vs. MPT, P = 0.04). The risk of having a TE infection of any grade and a TE grade ≥ 3 infection beyond 18 months of treatment was 31.8% (169 patients) and 9.2% (49 patients), respectively, with Rd continuous. The risk of a TE grade 5 infection during the first 18 months was 3.6% (19 patients) with Rd continuous, 3.3% (18 patients) with Rd18, and 2.6% (14 patients) with MPT (Rd pooled vs. MPT, P = 0.35). After 18 months of treatment, the risk of a TE grade 5 infection was 0.4% (two patients) with Rd continuous.

TE infections occurring during the first 4 months of treatment

The number of TE infections per month was highest during the first 4 months of treatment (Fig. 1a). A total of 1064 TE infections of any grade occurred during the first 4 months, including 265 TE grade ≥ 3 infections (representing 25.0% of 1061 TE infections of known grade) (Table 1). The lungs and respiratory tract were involved in 48.7% of early TE grade ≥ 3 infections, whereas 22.6% of these infections were localized to the blood, with patients exhibiting sepsis, bacteremia, and viremia (Supplemental Table 3). The pathogen was identified in 25.3% of early TE grade ≥ 3 infections; bacterial infections were implicated in 79.1% of cases in which a pathogen was identified (Supplemental Table 4). Streptococcal, staphylococcal, and clostridia infections were the most commonly specified bacterial infections. No statistical differences were seen between Rd pooled and MPT in the rates of staphylococcal and streptococcal infections (P = 0.25 and P = 0.15, respectively).
Fig. 1

Treatment-emergent (TE) infections in the FIRST trial. a Number of TE infections by month in the first 18 months of the FIRST trial (1613 treated patients). The numbers above the bars indicate the total number of TE infections of all grades during the treatment month. b Number of new patients with TE grade ≥ 3 infections by month in the first 18 months of the FIRST trial (1613 treated patients)

Treatment-emergent (TE) infections in the FIRST trial. a Number of TE infections by month in the first 18 months of the FIRST trial (1613 treated patients). The numbers above the bars indicate the total number of TE infections of all grades during the treatment month. b Number of new patients with TE grade ≥ 3 infections by month in the first 18 months of the FIRST trial (1613 treated patients) Overall, 56.2% of patients with a TE grade ≥ 3 infection in the first 18 months experienced their first infection in the first 4 months, and there were < 20 new patients with TE grade ≥ 3 infections per month after 4 months of treatment (Fig. 1b). A total of 191 patients (11.8%) experienced ≥ 1 TE grade ≥ 3 infection during the first 4 months of treatment (12.2% Rd pooled and 11.1% MPT, P = 0.51); 54 patients (3.3%) experienced > 1 TE grade ≥ 3 infection (Table 2).
Table 2

Rate of TE grade ≥ 3 infections by treatment arm in the FIRST trial (safety population)

Patients with indicated number of TE grade ≥ 3 infections, n (%)0–4 months0–18 monthsBeyond 18 months
Rd cont (n = 532)Rd18 (n = 540)MPT (n = 541)Total (N = 1 613)Rd cont (n = 532)Rd18 (n = 540)MPT (n = 541)Total (N = 1 613)Rd cont (n = 532)Rd18 (n = 540)MPT (n = 541)Total (N = 1 613)
0469 (88.2)472 (87.4)481 (88.9)1 422 (88.2)412 (77.4)418 (77.4)443 (81.9)1 273 (78.9)483 (90.8)539 (99.8)541 (100)1 563 (96.9)
146 (8.6)48 (8.9)43 (7.9)137 (8.5)72 (13.5)72 (13.3)64 (11.8)208 (12.9)35 (6.6)1 (0.2)036 (2.2)
213 (2.4)16 (3.0)8 (1.5)37 (2.3)28 (5.3)35 (6.5)22 (4.1)85 (5.3)10 (1.9)0010 (0.6)
 ≥ 34 (0.8)4 (0.7)9 (1.7)17 (1.1)20 (3.8)15 (2.8)12 (2.2)47 (2.9)4 (0.8)004 (0.2)

MPT melphalan, prednisone, and thalidomide, Rd cont lenalidomide plus low-dose dexamethasone until disease progression, Rd18 lenalidomide plus low-dose dexamethasone for 18 cycles, TE treatment emergent

Rate of TE grade ≥ 3 infections by treatment arm in the FIRST trial (safety population) MPT melphalan, prednisone, and thalidomide, Rd cont lenalidomide plus low-dose dexamethasone until disease progression, Rd18 lenalidomide plus low-dose dexamethasone for 18 cycles, TE treatment emergent Of the 57 TE grade five infections that occurred during the study (53 patients [3.3%]), 30 (52.6%) occurred during the first 4 months (28 patients [1.7%]).

Impact of first TE grade ≥ 3 infection in the first 4 months on OS

The risk of death associated with a first TE grade ≥ 3 infection in the first 4 months, as assessed in a time-dependent Cox regression analysis, was significant (HR, 2.9 [95% CI, 2.4–3.6]; P < 0.0001). A stepwise multivariate time-dependent analysis for baseline risk factors was then performed to adjust for potential confounding factors. The occurrence of a first TE grade ≥ 3 infection in the first 4 months remained significant in the final OS predictive model (HR, 9.1 [95% CI, 5.6-14.6]; P < 0.0001) (Supplemental Table 5).

Baseline factors associated with risk of ≥ 1 early TE grade ≥ 3 infection

Demographic and baseline characteristics of the intent-to-treat and prognostic analysis populations in MM-020 and the validation sets are presented in Supplemental Table 6. A comprehensive analysis was performed on the prognostic analysis population in MM-020 to identify risk factors associated with high or low risk of first TE grade ≥ 3 infection in the first 4 months using the Q-Finder algorithm (Supplemental Table 7). The most significant variables associated with a high or low risk of infection included Sβ2M levels or International Staging System stage, number of CRAB (hypercalcemia, renal failure, anemia, and bone lesions) diagnostic criteria [17], M-protein urine levels, creatinine or urea levels, red blood cell counts, hematocrit or hemoglobin levels, LDH levels, triiodothyronine (thyroid hormone; T3) levels, α-1 globulin levels, and eosinophil counts. Patients with low quality-of-life score at baseline also had a significantly increased risk of early grade ≥ 3 TE infection. An exploratory analysis of baseline immunoparesis on the risk of early grade ≥ 3 TE infection is presented in the Supplement (Immunoparesis and the Risk of Infection at 4 Months).

First TE grade ≥ 3 infection in the first 4 months scoring system

Of the statistically significant variables identified by the Q-Finder algorithm, clinical experts in MM selected variables with high clinical relevance to be proposed to the multivariate logistic regression model (Supplemental Table 8). The multivariate analysis, which included eight rules identified by the univariate analysis to be associated with high or low risk of early TE grade ≥ 3 infection (ECOG PS < 1, ECOG PS ≥ 2, Sβ2M ≥ 6 mg/L, Sβ2M ≤ 3 mg/L, LDH ≥ 200 U/L, hemoglobin ≤ 9 g/dL, hemoglobin ≥ 11 g/dL, and creatinine ≥ 1.2 mg/dL), showed that six rules based on ECOG PS and Sβ2M, LDH, and hemoglobin levels were independently associated with first TE grade ≥ 3 infection in the first 4 months (Table 3).
Table 3

Multivariate logistic regression model for first TE grade ≥ 3 infection during the first 4 months of treatment (1369 patients included)

VariableCoefficientaOdds ratioP-valuePointsInfection risk
EstimateSE
Sβ2M ≤ 3 mg/L−0.8120.3530.440.021−2Low
ECOG PS of 0−0.4030.2160.670.062−1Low
Hemoglobin ≤ 11 g/dL0.3660.2071.440.0771High
ECOG PS of ≥ 20.4570.1891.580.0161High
LDH ≥ 200 U/L0.5520.1861.740.0031High
Sβ2M ≥ 6 mg/L0.8200.1762.27 < 0.0012High

ECOG PS Eastern Cooperative Oncology Group performance status, LDH lactate dehydrogenase, Sβ2M serum β2-microglobulin, TE treatment emergent

a Coefficient in the multivariate logistic model

Multivariate logistic regression model for first TE grade ≥ 3 infection during the first 4 months of treatment (1369 patients included) ECOG PS Eastern Cooperative Oncology Group performance status, LDH lactate dehydrogenase, Sβ2M serum β2-microglobulin, TE treatment emergent a Coefficient in the multivariate logistic model From the resulting predictive model, a scoring system (Table 3) was used to create high (2 to 5 points) and low (−3 to 1 points) infection risk groups. The cutoff between these groups was selected based on the best sensitivity/specificity ratio. These high- and low-risk groups were associated with significantly different rates of early TE grade ≥ 3 infections (24.0% vs. 7.0%, respectively; P < 0.0001; C-index, 0.66; RR, 3.43 [95% CI, 2.57–4.59]; NNT, 8.3).

Validation of the predictive model for risk of first TE grade ≥ 3 infection in the first 4 months

When tested on three independent cohorts (MM-015, MM-009/010, and MM-003), [9, 11–13] the model discriminated between high- and low-risk patients regarding the risk of developing early TE grade ≥ 3 infection (Table 4), with comparable RRs between high- and low-risk groups in all three test sets (MM-015: RR, 2.05 [P = 0.055]; MM-003: RR, 2.09 [P < 0.0001]; MM-009/010: RR, 2.09 [P = 0.0008]). This was despite very different populations at baseline and different rates of early TE grade ≥ 3 infection (MM-015, 9.4%; MM-009-010, 20.3%; MM-003, 43.7%) compared with MM-020 (13.9%). Due to the difference in infection risks in those populations, the NNT differed greatly in the various populations (MM-015, 15.5; MM-009/010, 5.6; MM-003, 3.2) compared with MM-020 (8.3).
Table 4

TE grade ≥ 3 infections during the first 4 months of high- and low-risk populations in various studies

TrialGrade ≥ 3 infections, %P-value*low risk vs. high riskRR (95% CI)NNT
Low risk (−3 to 1 points)High risk (2 to 5 points)
MM-020 (N = 1 369)a7.024.08.19 × 10−193.43 (2.57–4.59)8.3
Rd pooled (n = 918)7.424.92.7 × 10−133.37 (2.39–4.76)8.0
MPT (n = 451)6.222.49.15 × 10−73.63 (2.11–6.24)8.9
MM-015 (n = 384)a6.312.90.05522.05 (1.07–3.92)15.5
MM-009/10 (n = 404)a17.135.77.69 × 10−42.09 (1.41–3.10)5.6
MM-003 (n = 222)a30.363.32.21 × 10−62.09 (1.54–2.83)3.2

MPT melphalan, prednisone, and thalidomide, NNT number needed to treat, Rd cont lenalidomide plus low-dose dexamethasone until disease progression, Rd18 lenalidomide plus low-dose dexamethasone for 18 cycles, Rd pooled Rd cont and Rd18 patients combined, RR relative risk, TE treatment emergent

*P-value computed with χ2 test

a Patients with missing data for ≥ 1 of the variables selected by the multivariate logistic regression were excluded from the high-/low-risk definition

TE grade ≥ 3 infections during the first 4 months of high- and low-risk populations in various studies MPT melphalan, prednisone, and thalidomide, NNT number needed to treat, Rd cont lenalidomide plus low-dose dexamethasone until disease progression, Rd18 lenalidomide plus low-dose dexamethasone for 18 cycles, Rd pooled Rd cont and Rd18 patients combined, RR relative risk, TE treatment emergent *P-value computed with χ2 test a Patients with missing data for ≥ 1 of the variables selected by the multivariate logistic regression were excluded from the high-/low-risk definition

Confirmatory analyses of the predictive model for risk of first TE grade ≥ 3 infection in the first 4 months

For illustration, a time to first infection analysis was performed in both the MM-020 and the independent validation sets (Fig. 2). In all test sets, patients in the high-risk group had a significantly shorter time to first TE grade ≥ 3 infection in the first 4 months compared with the low-risk group (MM-020: HR, 3.6 [P < 0.0001], C-index, 0.65; MM-003: HR, 2.7 [P < 0.0001], C-index, 0.64; MM-009/010: HR, 1.9 [P = 0.006], C-index, 0.57; MM-015: HR, 2.05 [P = 0.03], C-index, 0.59).
Fig. 2

Time to first grade ≥ 3 TE infection in the first 4 months for high- and low-risk groups in the a MM-020 (n = 1602), b MM-015 (n = 452), c MM-009/10 (n = 643), d MM-003 (n = 425) populations. C-index concordance index, HR hazard ratio

Time to first grade ≥ 3 TE infection in the first 4 months for high- and low-risk groups in the a MM-020 (n = 1602), b MM-015 (n = 452), c MM-009/10 (n = 643), d MM-003 (n = 425) populations. C-index concordance index, HR hazard ratio To confirm our predictive model, a competing risks analysis with progression or death without infection as competing events with first TE grade ≥ 3 infection in the first 4 months was performed using the MM-020 data set; this analysis included the same eight rules and iterative selection process used in the multivariate logistic analysis. The competing risk analysis in MM-020 confirmed the significance of the six rules as in the logistic model (Supplemental Table 9). As such, the competing risk analysis provided an identical model to the one obtained through logistic regression analysis. The final model remained significant (P < 0.05) in both the MM-020 and the independent validation sets in a competing risks analysis with progression or death without infection as competing events with first TE grade ≥ 3 infection in the first 4 months.

Discussion

Because infections remain an important cause of morbidity and mortality in patients with MM [1], analyses of large clinical trials can help identify risk factors associated with severe and life-threatening infections. The FIRST trial, which demonstrated a significant progression-free survival and OS benefit with Rd continuous vs. MPT, is among the largest phase 3 studies in MM and represents a typical transplant-ineligible NDMM population per its eligibility criteria; therefore, the prognostic factors of infection identified for these patients may be quite common in this population [7]. The FIRST trial confirmed that the risk of infection in MM is high: 65.4% of patients presented with ≥ 1 TE infection and 21.1% presented with ≥ 1 TE grade ≥ 3 infection. The risk of infection in the first 18 months was different across treatments: all TE infections (Rd pooled, 69.4%; MPT, 57.5% [P < .0001]) and TE grade ≥ 3 infections (Rd pooled, 22.6%; MPT, 18.1% [P = .04]). This was noted despite the higher rate of grade 3/4 neutropenia with MPT (44.9%) vs. Rd pooled (27.1%) [7]. Nearly 75% of all grade ≥ 3 infections occurred in the absence of neutropenia (data not shown), suggesting that dexamethasone may have a contributing role. This post hoc analysis showed that in the first 4 months of treatment, (1) of patients who experienced a TE grade ≥ 3 infection, the majority had their first infection during this time; (2) nearly one-half of all TE grade ≥ 3 infections occurred, including the majority of infection-related deaths; and (3) first TE grade ≥ 3 infection was associated with an increased risk of death, independent of prognostic factors for OS. Our results are consistent with previous studies that have shown that infections occur more often in the first and second months of treatment [18, 19]. Infection risk may be highest during this period due to the immunosuppressive nature of active MM and antimyeloma agents coupled with the likelihood that the antimyeloma agents have not yet maximally reduced tumor load and repaired organ and tissue damage [2, 18, 20]. The risk of early TE grade ≥ 3 infection was similar with Rd vs. MPT, highlighting the role of baseline patient-specific factors in determining infection risk during early treatment. Multivariate analysis identified ECOG PS and Sβ2M, LDH, and hemoglobin levels as prognostic factors for early TE grade ≥ 3 infection. The significance of these variables was confirmed by a competing risk analysis of first TE grade ≥ 3 infection and death or progression without infection during the first 4 months. Given that only 94 of the 3125 infections of any grade that occurred during the study were non-TE infections, it is unlikely that including non-TE infections in the analysis would alter the results. A risk-scoring system was used to separate patients in the FIRST trial into high- and low-risk groups, which were associated with significantly different rates of early TE grade ≥ 3 infections (24.0% vs. 7.0%, respectively). The predictive model differentiated high-risk from low-risk patients in three independent data cohorts, which included patients with relapsed/refractory MM (RRMM; MM-003 and MM-009/010) and NDMM (MM-015). As expected, the risk was greater in the three RRMM studies that used dexamethasone (high-dose dexamethasone in MM-009/010 and the control arm of MM-003 and low-dose dexamethasone in the pomalidomide arm of MM-003). Although still relevant, the model showed a lower absolute benefit in MM-015, which had a lower incidence of early TE grade ≥ 3 infections and used prednisone instead of dexamethasone. In the low-risk groups, the risk was similar in the MPT arms of MM-020 and MM-015, which investigated MP and MP+lenalidomide (6.2% and 6.3%, respectively). The risk was marginally higher in the Rd arms of MM-020 (7.4%) and highest in MM-009/010 and MM-003 (17.1% and 30.3 %, respectively). Similarly, RRMM studies had a significant risk of early TE grade ≥ 3 infections in the high-risk groups (up to 63.3% in the MM-003 study). Even though these findings should be interpreted cautiously, the results suggest that dexamethasone is a risk factor for early TE grade ≥ 3 infections, with studies with prednisone being associated with a lower risk. These post hoc analysis findings are informative; however, cautious interpretation is warranted. The use of antibiotic prophylaxis was neither mandated in the study protocol nor standardized, which may limit interpretability. A pathogen could not be specified in a substantial proportion of infections reported limiting further elucidation on the types of interventions that may be useful in this setting. Although it is common in MM trials and in practice that a substantial proportion of infections have no pathogen specified [21, 22], additional MM studies with data on infections with specified causes are needed to determine possible patterns of specific types of infections and appropriate preventative therapies for patients at risk. Our model also requires further prospective interrogation for additional validation, particularly in proteasome inhibitor-based studies. Furthermore, it would be of interest for additional studies to investigate risk factors for TE grade ≥ 3 infection after the first 4 months of treatment as just over half of all TE grade ≥ 3 infections occurred after the first 4 months in this study. In conclusion, a majority of patients in the FIRST trial reported ≥ 1 TE infection, confirming that the risk of TE infection in patients with MM is high. In addition, our analysis identified a set of baseline patient characteristics that were associated with risk of developing a TE grade ≥ 3 infection in the initial 4 months of treatment. The high- and low-risk groups defined by our scoring system were associated with significantly different infection rates, irrespective of treatment. Clinicians may be able to apply this model to adjust their monitoring and treatment strategies for infection prevention. The results of the predictive model could be integrated into current infection management guidelines, including those from the International Myeloma Working Group [23] and European Myeloma Network [24]. Future NDMM studies could apply this model to evaluate which patients (all or those at high infection risk) should receive prophylactic anti-infective drugs and what type would be most beneficial to each patient subpopulation.

Disclaimer

The authors were fully responsible for all content and editorial decisions for this manuscript. Supplement for Dumontet MM-020 Infections MS
  22 in total

1.  Perspectives in multiple myeloma: survival, prognostic factors and disease complications in a single centre between 1975 and 1988.

Authors:  H C Rayner; A P Haynes; J R Thompson; N Russell; J Fletcher
Journal:  Q J Med       Date:  1991-06

2.  European Myeloma Network guidelines for the management of multiple myeloma-related complications.

Authors:  Evangelos Terpos; Martina Kleber; Monika Engelhardt; Sonja Zweegman; Francesca Gay; Efstathios Kastritis; Niels W C J van de Donk; Benedetto Bruno; Orhan Sezer; Annemiek Broijl; Sara Bringhen; Meral Beksac; Alessandra Larocca; Roman Hajek; Pellegrino Musto; Hans Erik Johnsen; Fortunato Morabito; Heinz Ludwig; Michele Cavo; Hermann Einsele; Pieter Sonneveld; Meletios A Dimopoulos; Antonio Palumbo
Journal:  Haematologica       Date:  2015-10       Impact factor: 9.941

3.  Early mortality after diagnosis of multiple myeloma: analysis of patients entered onto the United kingdom Medical Research Council trials between 1980 and 2002--Medical Research Council Adult Leukaemia Working Party.

Authors:  Bradley M Augustson; Gulnaz Begum; Janet A Dunn; Nicola J Barth; Faith Davies; Gareth Morgan; Judith Behrens; Alastair Smith; J Anthony Child; Mark T Drayson
Journal:  J Clin Oncol       Date:  2005-11-07       Impact factor: 44.544

4.  Pomalidomide plus low-dose dexamethasone versus high-dose dexamethasone alone for patients with relapsed and refractory multiple myeloma (MM-003): a randomised, open-label, phase 3 trial.

Authors:  Jesus San Miguel; Katja Weisel; Philippe Moreau; Martha Lacy; Kevin Song; Michel Delforge; Lionel Karlin; Hartmut Goldschmidt; Anne Banos; Albert Oriol; Adrian Alegre; Christine Chen; Michele Cavo; Laurent Garderet; Valentina Ivanova; Joaquin Martinez-Lopez; Andrew Belch; Antonio Palumbo; Stephen Schey; Pieter Sonneveld; Xin Yu; Lars Sternas; Christian Jacques; Mohamed Zaki; Meletios Dimopoulos
Journal:  Lancet Oncol       Date:  2013-09-03       Impact factor: 41.316

Review 5.  Infection risk with immunomodulatory and proteasome inhibitor-based therapies across treatment phases for multiple myeloma: A systematic review and meta-analysis.

Authors:  Benjamin W Teh; Simon J Harrison; Leon J Worth; Karin A Thursky; Monica A Slavin
Journal:  Eur J Cancer       Date:  2016-09-01       Impact factor: 9.162

6.  Lenalidomide plus dexamethasone is more effective than dexamethasone alone in patients with relapsed or refractory multiple myeloma regardless of prior thalidomide exposure.

Authors:  Michael Wang; Meletios A Dimopoulos; Christine Chen; M Teresa Cibeira; Michel Attal; Andrew Spencer; S Vincent Rajkumar; Zhinuan Yu; Marta Olesnyckyj; Jerome B Zeldis; Robert D Knight; Donna M Weber
Journal:  Blood       Date:  2008-09-17       Impact factor: 22.113

7.  Final analysis of survival outcomes in the phase 3 FIRST trial of up-front treatment for multiple myeloma.

Authors:  Thierry Facon; Meletios A Dimopoulos; Angela Dispenzieri; John V Catalano; Andrew Belch; Michele Cavo; Antonello Pinto; Katja Weisel; Heinz Ludwig; Nizar J Bahlis; Anne Banos; Mourad Tiab; Michel Delforge; Jamie D Cavenagh; Catarina Geraldes; Je-Jung Lee; Christine Chen; Albert Oriol; Javier De La Rubia; Darrell White; Daniel Binder; Jin Lu; Kenneth C Anderson; Philippe Moreau; Michel Attal; Aurore Perrot; Bertrand Arnulf; Lugui Qiu; Murielle Roussel; Eileen Boyle; Salomon Manier; Mohamad Mohty; Herve Avet-Loiseau; Xavier Leleu; Annette Ervin-Haynes; Guang Chen; Vanessa Houck; Lotfi Benboubker; Cyrille Hulin
Journal:  Blood       Date:  2017-11-17       Impact factor: 22.113

8.  Influence of treatment and response status on infection risk in multiple myeloma.

Authors:  R T Perri; R P Hebbel; M M Oken
Journal:  Am J Med       Date:  1981-12       Impact factor: 4.965

Review 9.  Immunodeficiency and immunotherapy in multiple myeloma.

Authors:  Guy Pratt; Oliver Goodyear; Paul Moss
Journal:  Br J Haematol       Date:  2007-09       Impact factor: 6.998

10.  Continuous lenalidomide treatment for newly diagnosed multiple myeloma.

Authors:  Antonio Palumbo; Roman Hajek; Michel Delforge; Martin Kropff; Maria Teresa Petrucci; John Catalano; Heinz Gisslinger; Wiesław Wiktor-Jędrzejczak; Mamia Zodelava; Katja Weisel; Nicola Cascavilla; Genadi Iosava; Michele Cavo; Janusz Kloczko; Joan Bladé; Meral Beksac; Ivan Spicka; Torben Plesner; Joergen Radke; Christian Langer; Dina Ben Yehuda; Alessandro Corso; Lindsay Herbein; Zhinuan Yu; Jay Mei; Christian Jacques; Meletios A Dimopoulos
Journal:  N Engl J Med       Date:  2012-05-10       Impact factor: 91.245

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  19 in total

Review 1.  Treatment approach for the older, unfit patient with myeloma from diagnosis to relapse: perspectives of a European hematologist.

Authors:  Thierry Facon; Kenneth Anderson
Journal:  Hematology Am Soc Hematol Educ Program       Date:  2018-11-30

2.  Q-Finder: An Algorithm for Credible Subgroup Discovery in Clinical Data Analysis - An Application to the International Diabetes Management Practice Study.

Authors:  Cyril Esnault; May-Line Gadonna; Maxence Queyrel; Alexandre Templier; Jean-Daniel Zucker
Journal:  Front Artif Intell       Date:  2020-12-17

3.  Pathogen-Specific Humoral Immunity and Infections in B Cell Maturation Antigen-Directed Chimeric Antigen Receptor T Cell Therapy Recipients with Multiple Myeloma.

Authors:  Srirama Josyula; Margot J Pont; Sayan Dasgupta; Xiaoling Song; Sushma Thomas; Gregory Pepper; Jacob Keane-Candib; Terry L Stevens-Ayers; Hans D Ochs; Michael J Boeckh; Stanley R Riddell; Andrew J Cowan; Elizabeth M Krantz; Damian J Green; Joshua A Hill
Journal:  Transplant Cell Ther       Date:  2022-03-11

Review 4.  Treatment and disease-related complications in multiple myeloma: Implications for survivorship.

Authors:  Rajshekhar Chakraborty; Navneet S Majhail
Journal:  Am J Hematol       Date:  2020-03-13       Impact factor: 10.047

5.  A simple score to predict early severe infections in patients with newly diagnosed multiple myeloma.

Authors:  Cristina Encinas; José-Ángel Hernandez-Rivas; Albert Oriol; Laura Rosiñol; María-Jesús Blanchard; José-María Bellón; Ramón García-Sanz; Javier de la Rubia; Ana López de la Guía; Ana Jímenez-Ubieto; Isidro Jarque; Belén Iñigo; Victoria Dourdil; Felipe de Arriba; Clara Cuéllar Pérez-Ávila; Yolanda Gonzalez; Miguel-Teodoro Hernández; Joan Bargay; Miguel Granell; Paula Rodríguez-Otero; Maialen Silvent; Carmen Cabrera; Rafael Rios; Adrián Alegre; Mercedes Gironella; Marta-Sonia Gonzalez; Anna Sureda; Antonia Sampol; Enrique M Ocio; Isabel Krsnik; Antonio García; Aránzazu García-Mateo; Joan-Alfons Soler; Jesús Martín; José-María Arguiñano; María-Victoria Mateos; Joan Bladé; Jesús F San-Miguel; Juan-José Lahuerta; Joaquín Martínez-López
Journal:  Blood Cancer J       Date:  2022-04-19       Impact factor: 9.812

6.  Identification of subgroups of patients with type 2 diabetes with differences in renal function preservation, comparing patients receiving sodium-glucose co-transporter-2 inhibitors with those receiving dipeptidyl peptidase-4 inhibitors, using a supervised machine-learning algorithm (PROFILE study): A retrospective analysis of a Japanese commercial medical database.

Authors:  Fang L Zhou; Hirotaka Watada; Yuki Tajima; Mathilde Berthelot; Dian Kang; Cyril Esnault; Yujin Shuto; Hiroshi Maegawa; Daisuke Koya
Journal:  Diabetes Obes Metab       Date:  2019-06-03       Impact factor: 6.577

7.  Low neutralizing antibody responses against SARS-CoV-2 in older patients with myeloma after the first BNT162b2 vaccine dose.

Authors:  Evangelos Terpos; Ioannis P Trougakos; Maria Gavriatopoulou; Ioannis Papassotiriou; Aimilia D Sklirou; Ioannis Ntanasis-Stathopoulos; Eleni-Dimitra Papanagnou; Despina Fotiou; Efstathios Kastritis; Meletios A Dimopoulos
Journal:  Blood       Date:  2021-07-01       Impact factor: 22.113

8.  Bortezomib-based induction, high-dose melphalan and lenalidomide maintenance in myeloma up to 70 years of age.

Authors:  Elias K Mai; Kaya Miah; Uta Bertsch; Jan Dürig; Christof Scheid; Katja C Weisel; Christina Kunz; Markus Munder; Hans-Walter Lindemann; Maximilian Merz; Dirk Hose; Anna Jauch; Anja Seckinger; Steffen Luntz; Sandra Sauer; Stephan Fuhrmann; Peter Brossart; Ahmet Elmaagacli; Martin Goerner; Helga Bernhard; Martin Hoffmann; Marc S Raab; Igor W Blau; Mathias Hänel; Axel Benner; Hans J Salwender; Hartmut Goldschmidt
Journal:  Leukemia       Date:  2020-07-20       Impact factor: 11.528

9.  Multiple myeloma and infection: this association is still close.

Authors:  Marcia Garnica
Journal:  Hematol Transfus Cell Ther       Date:  2019-10-08

10.  The neutralizing antibody response post COVID-19 vaccination in patients with myeloma is highly dependent on the type of anti-myeloma treatment.

Authors:  Evangelos Terpos; Maria Gavriatopoulou; Ioannis Ntanasis-Stathopoulos; Alexandros Briasoulis; Sentiljana Gumeni; Panagiotis Malandrakis; Despina Fotiou; Eleni-Dimitra Papanagnou; Magdalini Migkou; Foteini Theodorakakou; Maria Roussou; Evangelos Eleutherakis-Papaiakovou; Nikolaos Kanellias; Ioannis P Trougakos; Efstathios Kastritis; Meletios A Dimopoulos
Journal:  Blood Cancer J       Date:  2021-08-02       Impact factor: 11.037

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