J Cancer 2018; 9(12):2211-2214. doi:10.7150/jca.24288

Short Research Communication

Multiple Myeloma Index for Risk of Infection

Valkovic T1, Gacic V2, Nacinovic-Duletic A1 Corresponding address

1. Department of Hematology, Rheumatology and Clinical Immunology, University Hospital Center Rijeka and School of Medicine Rijeka, Croatia
2. Department of Hematology, University Hospital Center Mostar, Bosnia and Hercegovina

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How to cite this article:
T V, V G, A ND. Multiple Myeloma Index for Risk of Infection. J Cancer 2018; 9(12):2211-2214. doi:10.7150/jca.24288. Available from http://www.jcancer.org/v09p2211.htm

Abstract

Based on our earlier research into the main characteristics and risk factors for infections in hospitalized patients with multiple myeloma, we created the numerical Multiple Myeloma Index for Risk of Infection (MMIRI) to predict infection in myeloma patients. The included factors that could influence the pathogenesis and incidence of infections were sex, performance status, Durie Salmon stage of disease, International Staging System, serum creatinine level, immune paresis, neutropenia, serum ferritin level, the presence of any catheters, disease duration, stable/progressive disease, and type of therapy. For each of these parameters, the strength of association with infection was statistically estimated and specific number of points was assigned to each of these parameters, proportional to the strength of the association. When designing the MMIRI, we included only those parameters that we determined were pathophysiologically associated with the infection. After further statistical analysis, we identified an optimal cutoff score of 6 or above as indicating a significant risk for infection, with a sensitivity of 93.2% and specificity of 80.2%. The scoring system in the retrospective receiver operating characteristic analysis showed an area under the curve of 0.918. The potential value of the MMIRI is the possibility of identifying those patients who would benefit from the prophylactic administration of antibiotics and other anti-infective measures while minimizing the contribution to antibiotic resistance related to the overuse of these drugs. As far as we know, this index represents the first attempt to create such an instrument for predicting the occurrence of infections in myeloma patients.

Introduction

The intrinsic immune dysfunction in combination with therapy-related immunosuppression leads to an increased risk for infections, which is a hallmark of multiple myeloma (MM) and major cause of mortality [1-5]. Furthermore, the infection itself can pathogenetically contribute to the progression of MM through different mechanisms, such as robust production of promyeloma cytokines (e.g., interleukin-6) and activation of Toll-like receptors on malignant plasma cells [6-10]. Today, with the advent of several new and effective antimyeloma drugs and increased overall survival, preventing death from infections becomes paramount. We tried to create the numerical Multiple Myeloma Index for Risk of Infection (MMIRI) to predict infection in myeloma patients and help identify patients who have a higher risk for developing infections.

Materials and Methods

To develop the index, we used our earlier research into the main characteristics and risk factors for infections in hospitalized patients with MM [11]: we took retrospective data from hospital medical documentation for 240 cases of hospitalized patients with MM (120 males and 120 females; average age of 69, range of 41-89 years) who were diagnosed or treated in our Department from January 2008 to December 2010. Because the majority of patients were hospitalized more than once, the total number of our cases was larger than the number of patients included in this study (37 males and 35 females, respectively). Only patients who were not treated with autologous or allogeneic hematopoietic stem cell transplant were included. The diagnosis was established according to International Myeloma Working Group criteria [12]. The great majority of patients in this study had IgG, IgA, or a light-chain myeloma; however, one patient with IgD and one with nonsecretory myeloma were also included [11]. Our patients were treated fairly uniformly at the time of this study: vincristine, doxorubicin, and dexamethasone and oral melphalan and prednisone regimens were mostly used as induction therapy (according to patient age and eligibility for high-dose therapy), with thalidomide-based protocols as second-line therapy and bortezomib-based protocols as third- or next-line therapy. In some patients, monotherapy with dexamethasone was used as a front-line therapy, as well as for postinduction [11]. The study was approved by the Medical School of Rijeka Ethics Committee.

The criteria for infection used in our study were increased body temperature above the normal range (37 °C) or isolation of a microbial agent in patients who also had concomitant clinical symptoms and/or humoral signs of infection (leukocytosis, neutrophilia, marked “left shift,” or increased C-reactive protein in comparison with a baseline value) [11]. The included factors that could influence the pathogenesis and incidence of infections were sex, performance status [13], Durie Salmon stage of disease [14], International Staging System [15], serum creatinine level (normal or increased), immune paresis defined qualitatively (decreased serum concentration of any polyclonal Ig class), neutropenia (defined as blood neutrophil count of ≤2×109/L), serum ferritin level (normal; moderately increased; extremely increased), the presence of any catheters, disease duration, stable/progressive disease, and type of therapy. The number of cases, age, sex, and duration of disease for MM patients with and without infections are presented in Table 1. The characteristics of tested parameters are shown in Table 2 [11].

For each of these parameters, the strength of association with infection was statistically estimated. When designing the MMIRI, we included only those parameters that we determined were pathophysiologically associated with the infection. A specific number of points was assigned to each of these parameters, proportional to the strength of the statistical association. Statistical association between nominal variables was measured by Cramer's V coefficient, whereby a minimum coefficient value of 0.15 was required. For the scoring system, the coefficient values were divided by a minimum value and rounded to the nearest integer. The cutoff value of the scoring system was determined by optimization of sensitivity and specificity based on the Youden index together with classical receiver operating characteristic analysis.

 Table 1 

Main cases characteristics

With infectionsWithout infectionsTotal
Number of cases43197240
Age, median (range)65 (41-89)69 (41-86)69 (41-89)
Sex (male/female), n9/34111/86120/120
Disease duration (months), median (range)26 (1-121)7 (1-150)8 (1-150)
 Table 2 

Characteristics of tested parameters

Tested ParametersNumber of CasesGroup without InfectionsGroup with Infections
SexMale1201119
Female1208634
ECOG
performance status
016160
188853
2706010
3453015
420515
Durie-Salmon stage of disease1A651
2A51474
2B101
3A1068917
3B594019
International Staging
System
1544410
257507
3988117
Serum creatinine level≤100 mmol/L (f); ≤120 mmol/L (m) (normal value)13311716
>100≤175 mmol/L (f); >120≤175 mmol/L (m)524111
>175 mmol/l (f, m)493514
ImmuneparesisYes18414836
No46406
NeutropeniaNo16013822
1.01-2x109/L554411
0.51-1x109/L1486
<0.5x109/L312
Serum ferritin level≤120 μg/L (f); ≤300 μg/L (m)51465
>120≤240 μg/L (f); > 300≤600 μg/L (m)19163
>240 μg/L (f); >600 μg/L (m)321814
Types of therapyWithout therapy39327
VAD76715
MP13112
Thalidomide-based20173
Dexamethasone55487
Bortezomib-based281414
Others514
Presence of any cathetersWithout catheters19017911
UC322210
CVC220
UC, CVC, ITC202
CVC, ITC110
UC, CVC808

f: female, m: male; VAD: vincristine, doxorubicin, dexamethasone, MP: oral melphalan and prednisone, UC: urinary catheter, CVC: central venous catheter, ITC: intrathoracic catheter

Results

We provide the relevant parameters associated with infections in the statistical analysis and the corresponding number of points assigned in the MMIRI in Table 3. Some other parameters, such as immune paresis and the International Staging System, showed no association with infections, and the parameters of sex and type of therapy were excluded from further analysis based on our determination that they were not useful. With these adjustments, we identified an optimal cutoff score of 6 or above as indicating a significant risk for infection, with a sensitivity of 93.2% and specificity of 80.2%. The scoring system in the retrospective receiver operating characteristic analysis showed an area under the curve of 0.918 (p<0.0001; Figure 1).

 Table 3 

Parameters associated with infections included in the MMIRI point system with corresponding points assigned for each parameter

ParameterCramer V coefficientPoints
Longer duration of disease
(>8 months)
0.23262
Durie Salmon Clinical
Stage 3B
0.19751
ECOG0 and 1-0.2935-2
ECOG2-0.06710
ECOG30.18621
ECOG40.44163
Presence of catheter0.65395
Elevated creatinine value0.15451
Moderately elevated ferritin value:
>120 to ≤240 μg/L (f)
>300 to ≤600 μg/L (m)
0.30122
Extremely elevated ferritin value:
>240 μg/L (f)
>600 μg/L (m)
0.38343
Neutropenia0.14181
Progressive disease0.32062
 Figure 1 

Testing of MMIRI by determining its sensitivity and specificity

J Cancer Image (Click on the image to enlarge.)

Discussion

The proposed index was created based on retrospective data from our specific hospital environment. As noted, the parameter of sex was excluded from further analysis; based on our findings, its association with infections in our sample was indirect because of its link with the other infection-relevant factors already incorporated into the MMIRI (e.g., the women included in our research more often had a certain kind of catheter). The parameter of type of therapy was also excluded because some regimens used at the time of our study are now obsolete, and the type and sequence of drugs and regimens used today are somewhat different. So far, it is well known that some therapies may be associated with the occurrence of infections (e.g. herpes zoster in patients treated with proteasome inhibitors or high-dose dexamethasone, for which effective antiviral prophylaxis is mandatory). Some recent papers show a possible association of some novel drugs with infection [16-25]. Thus, a possible causative link between certain drugs and infection occurrence must be investigated in further clinical studies, and the results can be incorporated into a subsequent modification of the proposed index.

Because transplanted patients were excluded, this index can be applied only to those patients who are not in the process of hematopoietic stem cell transplant or just post transplantation. Nevertheless, we believe that this index has great potential to help identify patients who have a higher risk for developing infections and to improve outcomes for myeloma patients. According to the present results, the patients with score of 6 or above are candidates for mandatory antimicrobial prophylaxis, which is the main message of this research. MMIRI and the total score can facilitate decision making about the timing of antimicrobial prophylaxis and other anti-infective measures (e.g., immunoglobulin, granulocyte growth factors). This index was created based on retrospective data, and our next step is to test it prospectively with a larger group of patients treated with currently used anti-myeloma drugs and regimens.

Acknowledgements

This work was supported by the Research Support of the University of Rijeka: grant No. 847.10.1347

Competing Interests

The authors have declared that no competing interest exists.

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Author contact

Corresponding address Corresponding author: Toni Valkovic, MD, PhD, Professor, Department of Hematology, Rheumatology and Clinical Immunology, University Hospital Center Rijeka and School of Medicine Rijeka, Kresimirova 42, 51000 Rijeka, Croatia. Telephone: 0038551658185; Fax: 0038551658826; e-mail: toni_valhr


Received 2017-12-10
Accepted 2018-2-10
Published 2018-6-4