Inflammatory Markers and Development of Symptom Burden in Patients with Multiple Myeloma during Autologous Stem Cell Transplantation

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1 Cancer Therapy: Clinical Clinical Cancer Research Inflammatory Markers and Development of Symptom Burden in Patients with Multiple Myeloma during Autologous Stem Cell Transplantation Xin Shelley Wang 1, Qiuling Shi 1, Nina D. Shah 2, Cobi J. Heijnen 1, Evan N. Cohen 3, James M. Reuben 3, Robert Z. Orlowski 4, Muzaffar H. Qazilbash 2, Valen E. Johnson 5, Loretta A. Williams 1, Tito R. Mendoza 1, and Charles S. Cleeland 1 Abstract Purpose: Increasing research suggests that inflammation mediates symptom development. In this longitudinal study, we examined inflammatory factors related to the development of high symptom burden during autologous hematopoietic stem cell transplant (AuSCT) for multiple myeloma. Experimental Design: Patients (n ¼ 63) repeatedly reported symptom severity on the MD Anderson Symptom Inventory multiple myeloma module (MDASI-MM) and contributed blood samples periodically for up to 100 days after AuSCT for inflammatory marker assays. The temporal associations between serum inflammatory marker concentrations and symptom severity outcomes were examined by nonlinear mixedeffect modeling. Results: Fatigue, pain, disturbed sleep, lack of appetite, and drowsiness were consistently the most severe MDASI-MM symptoms during the study. Peak symptom severity occurred on day 8 after AuSCT, during white blood cell count nadir. Patterns of serum interleukin (IL)-6 (peak on day 9) and soluble IL-6 receptor (sil-6r; nadir on day 8) expression paralleled symptom development over time (both P < ). By univariate analysis, serum IL-6, sil-6r, IL-10, C-reactive protein, macrophage inflammatory protein (MIP)- 1a, sil-1r2, sil-1ra, and soluble tumor necrosis factor receptor 1 were significantly related to the most severe symptoms during the first 30 days after AuSCT (all P < 0.05). By multivariate analysis, IL-6 (estimate ¼ 0.170; P ¼ 0.004) and MIP-1a (estimate ¼ 0.172; P ¼ 0.006) were temporally associated with the severity of the component symptom score. Conclusions: Systemic inflammatory response was associated with high symptom burden during the acute phase of AuSCT. Additional research is needed to understand how the inflammatory response is mechanistically associated with symptom expression and whether suppression of this response can reduce symptoms without compromising tumor control. Clin Cancer Res; 1 9. Ó2014 AACR. Introduction High-dose chemotherapy followed by autologous hematopoietic stem cell transplant (AuSCT) has become part of the standard treatment regimen for patients with multiple myeloma (1). As aggressive cancer therapies, both AuSCT and allogeneic stem cell transplant (AlloSCT) are Authors' Affiliations: Departments of 1 Symptom Research, 2 Stem Cell Transplantation, 3 Hematopathology, 4 Lymphoma/Myeloma, and 5 Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas Current address for E.N. Cohen: Department of Biomedical Engineering, The University of Texas, Austin, Texas; current address for V.E. Johnson, Department of Statistics, Texas A&M University, College Station, Texas. Corresponding Author: Xin Shelley Wang, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 1450, Houston, TX Phone: ; Fax: ; xswang@mdanderson.org doi: / CCR Ó2014 American Association for Cancer associated with the occurrence of high symptom burden in the initial weeks posttransplant, including fatigue, pain, disturbed sleep, poor appetite, and drowsiness (2, 3), despite the differences in therapeutic agents and stem cell sources. These symptoms are difficult to manage, due in part to limited knowledge of the pathophysiology underlying their development. Mounting evidence from both animal models and human research suggests that dysregulation of inflammatory processes may play a pivotal role in producing chronic systemic conditions, such as poor appetite, pain, fatigue, and disturbed sleep (4 6). Our studies of patients who rapidly developed severe symptoms in response to aggressive cancer therapy (chemoradiation for gastrointestinal or lung cancer and AlloSCT for hematologic malignancies) have shown that a significant increase in serum inflammatory cytokines such as interleukin (IL)-6 and soluble tumor necrosis factor receptor 1 (stnf-r1) is temporally associated with the development of severe symptoms during treatment (3, 7, 8). Consistent behavioral observations in OF1

2 Wang et al. Translational Relevance Inadequate understanding of the mechanisms underlying the development of severe symptoms has limited our ability to reduce symptom burden during aggressive cancer therapy. The cytokine response in animal models of "sickness behavior" demonstrates how increased systemic inflammation induces behaviors that resemble the symptoms patients report when they receive cancer treatment, suggesting a model for studying inflammation as a potential mechanism underlying the production of severe treatment-related symptoms. We demonstrate in this longitudinal study that serum interleukin-6 and a variety of inflammatory changes were temporally related to the most severe symptoms (fatigue, poor appetite, pain, distress, and disturbed sleep) in the acute phase (first 30 days) after autologous hematopoietic stem cell transplant for multiple myeloma. These findings raise the possibility that modulating components of inflammation during the acute phase of aggressive therapy may modulate treatment-related symptoms, so long as this can be done without compromising tumor control. these clinical studies parallel the cytokine-induced sickness behaviors, such as hyperalgesia, disturbed sleep, reduced water and food intake, and lack of activity, seen in animal models (5). In the current study, we studied patients with multiple myeloma undergoing high-dose chemotherapy with AuSCT by temporally tracking changes in inflammatory markers and their relationship with the development of severe symptoms. AuSCT presents a unique opportunity for studying the cytokine dysregulation induced by high-dose chemotherapy without interference from the acute graftversus-host response associated with AlloSCT (3). Patients and Methods Patients Patients were enrolled from 2008 to 2011 in the outpatient clinic of the Department of Stem Cell Transplantation at The University of Texas MD Anderson Cancer Center in Houston, Texas. Eligible patients had a confirmed pathologic diagnosis of multiple myeloma, were at least 18 years old, and most were scheduled to receive high-dose melphalan (200 mg/m 2 ) as their conditioning regimen for AuSCT. Patient characteristics and clinical parameters [age, sex, cancer stage, Eastern Cooperative Oncology Group performance status (ECOG PS; ref. 9, Charlson comorbidity score (10), induction treatment history, and body mass index (BMI)] were recorded during the study. The study was approved by the MD Anderson Institutional Review Board, and all participants gave written informed consent. The study is registered at Clinical- Trials.gov (NCT ). Multisymptom Assessment The MD Anderson Symptom Inventory (MDASI) assesses the severity of 13 common cancer-related symptoms (pain, fatigue, nausea, vomiting, dry mouth, shortness of breath, lack of appetite, difficulty remembering, drowsiness, disturbed sleep, sadness, distress, and numbness) and six items related to symptom interference with functioning (11). For this study, we used the psychometrically validated multiple myeloma module of the MDASI (MDASI-MM), which contains the 19 MDASI items plus 7 multiple myeloma specific items (bone aches, muscle weakness, sore mouth/ throat, rash, difficulty concentrating, constipation, and diarrhea) (12). Patients rated symptom severity over the previous 24 hours on a 0 to 10 scale ranging from "not present" to "as bad as you can imagine." MDASI-MM assessments were conducted at baseline (18 days before the transplant; day 18), twice a week from baseline to 30 days after AuSCT (day þ30), and then weekly until 100 days after AuSCT (day þ100). The assessments were completed on paper or, when the patient was unavailable in person, via phone interview with study staff. Inflammatory marker assay We assessed IL-1b, soluble IL-1 receptor antagonist (sil- 1RA), soluble IL-1 receptors 1 (sil-1r1) and 2 (sil-1r2), soluble IL-2 receptor antagonist (sil-2ra), IL-4, IL-6 and its soluble receptor sil-6r, IL-8, IL-10, IL-12p70, IL-17, TNF-a, stnf-r1, stnf-r2, interferon (IFN)-g, C-reactive protein (CRP), vascular endothelial growth factor (VEGF), macrophage inflammatory protein (MIP)-1a, and monocyte chemotactic protein (MCP)-1. These inflammatory markers have been identified as potentially relevant in animal and human sickness behavior studies (3, 5, 6, 13, 14). Blood draws without anticoagulant were scheduled for the morning on the day of apheresis, at mobilization and conditioning day, twice a week from stem cell transplant (day 0) to day þ30, and at routine clinic visits thereafter to day þ100. After serum isolation by centrifugation (2 4 hours after phlebotomy), the samples were stored at 80 C for batch analysis. Inflammatory markers were measured in 25 ml of serum using the MILLIPLEX MAP assays (EMD Millipore Corporation) and a Luminex 100 Analyzer (Luminex Corporation) (15). IL-1b, IL-4, IL-6, IL-8, IL-10, IL-12p70, IFN-g, and TNF-a were measured using the Millipore magnetic Human High-Sensitivity Cytokine/Chemokine Panel. IL-17, VEGF, MCP-1 and MIP-1a were quantified using the Millipore Human Cytokine/Chemokine Panel 1. The Millipore nonmagnetic Human Soluble Cytokine Receptor Panel was used to measure sil-1r1, sil-1r2, sil-2ra, sil-6r, stnf-r1, and stnf-r2. CRP, a by-product of inflammation, was measured in 1:27,000 diluted serum sample before analysis using the Human Cardiovascular Disease Panel 2. sil-1ra was measured in 100 ml of serum by enzyme-linked immunosorbent assay (R&D Systems, Inc.). OF2 Clin Cancer Res; 2014 Clinical Cancer Research

3 Inflammation and Symptoms in Autologous Stem Cell Transplant Statistical analysis To analyze the development of patient-reported symptom outcomes in relation to objective measures, we constructed loess curves to depict the mean level of symptom severity, white blood cell (WBC) count, and serum inflammatory marker levels from baseline to day þ100 after AuSCT (where day of stem cell transplant was designated as day 0). Nonlinear mixed modeling was used to determine WBC nadir, symptom peaks, and the peaks and nadirs in serum levels of inflammatory markers from baseline to day þ30. Statistical significance was set at (0.05/13.00) to adjust for multiple comparisons. We focused on the first 30 days posttransplant because most of the marker samples were collected during that time period and because graphed data for most of the symptoms and markers plateaued after day þ30. Mean MDASI-MM symptom severities and mean inflammatory marker concentrations between the day 18 to day þ30 period (before and the first month after AuSCT) and the period of symptom and marker plateau (day þ31 to day þ100) were reviewed using the Wilcoxon rank sum test. Descriptive analysis was used to present patient characteristics. Markers for which more than 10% of the samples had undetectable values were not included in the analysis. For each marker retained for analysis, samples with undetectable values were imputed to have one-half the lowest nonzero value from the detectable samples for that marker. To give context to the variability of the cytokine assay and symptoms, a waterfall plot was constructed to examine the changes in the five most severe symptoms and in serum IL-6 levels from baseline to nadir (16). To determine the relationship of the strength of inflammatory changes and increases in symptom severity, mixedeffect models were constructed to identify the critical serum inflammatory marker(s) that were temporally associated with symptoms with dynamic changes in the first 30 days, included as time-dependent variables (17). We used both MDASI-MM single-symptom scores and a mean component score of the five most severe symptoms as outcome measures for each patient. Time-independent variables that might have an impact on symptom or inflammatory response (age, sex, cancer stage, bortezomib induction treatment status, stem cell dose, baseline mood score, and BMI) were included in all models. The baseline mood score was the average of pre-ausct MDASI-MM "sadness" and "distress" scores, based on a previous study by McGregor et al. (18) indicating that distress had a significant effect on blood count recovery. Each inflammatory marker was included in a univariate model on a transformed natural log scale. Those that showed significant effects at P < 0.05 in the univariate models were included in a multivariate model for each symptom outcome. Statistical significance for each multivariate model was set as 0.05/n (where n is the number of cytokines included in the model). Estimates were calculated for natural log-transformed inflammatory marker variables to show how the symptom outcome would change when the marker changed by any ratio. Results Patient and treatment characteristics Of 70 eligible patients, 7 declined to participate. Table 1 presents the demographic and clinical characteristics of the remaining 63 participants enrolled pre-ausct. Four of the 63 patients withdrew from the study by day þ30 and 9 patients withdrew between days þ31 and þ100. WBC nadir was observed on day þ8 (range, 4 10 days). No disease Table 1. Patient characteristics (n ¼ 63) Patient characteristics n (%) Age Mean (SD) (8.19) Median, range ( ) <60 36 (57.14) (42.86) BMI Mean (SD) (7.13) Median, range 28.7 ( ) Stem cell dose (10 6 /kg) Mean (SD) 4.83 (1.86) Median, range 4.5 ( ) Pre-AuSCT mood score a Mean (SD) 1.74 (2.20) Median, range 0.5 ( ) Gender Male 41 (65.08) Female 22 (34.92) Race White 50 (79.37) Other 13 (20.63) Education Less than college 13 (20.63) College 33 (52.39) Graduate school 17 (26.98) ECOG PS score 0 11 (18.03) 1 40 (65.57) 2 10 (16.40) Cancer stage (ISS) I 32 (54.24) II 14 (23.73) III 13 (22.03) Charlson comorbidity score 0 40 (63.49) 1 14 (22.22) 2þ 9 (14.29) Induction regimen Bortezomib based 53 (84.13) Lenalidomide based 8 (12.70) Other 2 (3.17) Abbreviation: ISS, International Staging System for MM. a Defined as the component score of distress and sadness from the baseline MDASI-MM assessment. Clin Cancer Res; 2014 OF3

4 Wang et al. Figure 1. Loess curves of the estimated severity levels of multiple symptoms and WBC count between baseline (day 18) and day þ100 after AuSCT. relapse or death occurred during the first 100 days after AuSCT. Most of the patients had received bortezomib-based induction therapy (53, vs. 8 on lenalidomide). Almost all patients received melphalan 200 mg/m 2 as conditioning; 3 patients also received other agents in combination with melphalan. Patterns of symptom development The overall missing-data rate for MDASI-MM symptom ratings was 7% between baseline and day þ30 and 15% between days þ31 and þ100, stemming primarily from missed follow-up calls to patients. Comparing average mean MDASI-MM scores from baseline to day þ30, the five most severe symptoms were fatigue, disturbed sleep, pain, lack of appetite, and drowsiness; this ranking remained consistent throughout the study. Loess curves present the average WBC count and the projected severity of these five symptoms on a 0 to 10 scale from baseline to day þ100 (Fig. 1). Mixed-effects modeling demonstrated that lack of appetite displayed the largest change over time (linear terms for days since AuSCT, estimate ¼ 3.86, SE of the mean ¼ 0.42, P < ). We also examined day of peak symptom severity for the five most severe symptoms during the first 30 days after AuSCT (Table 2). The individual symptoms and the component score showed significant peaks around day þ8. Pain, one of the most severe symptoms, remained relatively constant over the observation period. Serum inflammatory marker patterns over time All cytokines that were below the limit of detection in more than 10% of the samples were excluded from the analysis. MCP-1, IL-8, TNF-a, sil-1ra, sil-1r2, sil-2ra, sil-6r, stnf-r1, stnf-r2, and CRP (each undetectable in <2% of the samples), MIP-1a (5.5%), IL-10 (6.5%), and IL- 6 (9%) were included in the analyses. Loess curves depict the average levels of inflammatory markers from baseline to day þ100 (Fig. 2). The markers presented in the figure were those found to have significant associations with symptom outcomes in both the univariate and multivariate analyses. Table 3 shows that the 13 testable inflammatory markers reached peak or nadir on various days after AuSCT. Because of these fluctuations, we Table 2. Nonlinear mixed modeling: peaks in the five most severe symptoms a during the first 30 days after AuSCT Symptom Estimated peak (days from transplant) 95% CI P Symptoms with significant peak All 5 symptoms < Fatigue < Lack of appetite < Disturbed sleep Drowsiness < Symptoms with no significant peak Pain Abbreviation: CI, confidence interval. a Fatigue, disturbed sleep, pain, lack of appetite, and drowsiness. OF4 Clin Cancer Res; 2014 Clinical Cancer Research

5 Inflammation and Symptoms in Autologous Stem Cell Transplant Figure 2. Changes in serum cytokine concentrations between baseline (day 18) and day þ100 after AuSCT. concentrated on data from baseline to day þ30 using nonlinear mixed modeling. Significant peak values were detected for IL-6 on day þ9, CRP on day þ13, and IL-10 on day þ18 (all P < ). A significant nadir was seen for sil-6r on day þ8 (P < ) and for sil-1ra on day þ5 (P ¼ 0.003). No significant peak or nadir was found for IL-8; however, the Wilcoxon rank sum test showed significantly lower levels of IL-8 during the first 30 days after AuSCT than from day þ31 to day þ100 (P ¼ ). Significantly higher concentrations of stnf-r1 (P ¼ 0.006) and sil-2ra (P < ) were found in the first 30 days after AuSCT than in Clin Cancer Res; 2014 OF5

6 Wang et al. Table 3. Nonlinear mixed modeling: peak or nadir of inflammatory markers during the first 30 days after AuSCT Inflammatory marker Estimated peak or nadir (days from transplant) 95% CI P Markers with significant peak IL < CRP < IL < Markers with significant nadir sil-1ra sil-6r < Markers with no significant peak or nadir IL stnf-r stnf-r MCP TNF-a MIP-1a sil-1r sil-2ra Abbreviation: CI, confidence interval. the later period. No significant change over time was observed for MCP-1, sil-1r2, or TNF-a. Associations between inflammatory markers and symptom severity Figure 3 presents a waterfall plot of the change scores from baseline to nadir. Most patients had increased symptom burden that was paralleled by increased proinflammatory response. The only outlier had an increased IL-6 level at baseline of pg/ml, corresponding with the patient s baseline clinical status (hypertensive, tachypneic, slightly tachycardic, and hyperglycemic). However, this patient also showed parallel changes of improved conditions with decreased symptoms and decreased cytokines over time. Univariate analysis identified serum IL-6, sil-6r, IL-10, CRP, MIP-1a, sil-1r2, and stnf-r1 (all P < 0.05) as significantly related to one or more of the five most severe symptoms during the first 30 days after AuSCT (Table 4). Age, sex, BMI, bortezomib versus other induction treatment, stem cell dose, pre-ausct mood score, and cancer stage were used as covariates, but there was no observed significant effect on symptom outcomes. The identified markers were retained as candidates for the multivariate analysis. The multivariate analysis (mixed effect modeling) identified IL-6 (P ¼ 0.001) and MIP-1a (P ¼ 0.013) as the critical Change in symptom severity inflammatory markers related to the development of the five most severe symptom outcomes during the first 30 days after AuSCT, controlling for the same set of covariates. Worse pre-ausct mood score was significantly associated with more severe symptom outcomes (P ¼ 0.003). The other covariates did not have a significant effect. For individual symptom outcomes, we found significant positive relationships between change in IL-6 concentration level and change in drowsiness (P ¼ 0.009) and between stnf-r1 (P ¼ 0.004) and IL-10 (P ¼ 0.01) related to higher pain severity; inverse relationships were found between MIP-1a and disturbed sleep (P ¼ ), and sil-6r and fatigue (P ¼ 0.039). Pre-AuSCT mood score was the only patient or clinical factor significantly related to changes in symptom severity (fatigue and drowsiness), although younger patients (60 years of age) consistently reported more severe pain than did older patients across the observation period (estimate ¼ 0.106; P ¼ 0.007). Discussion The current study suggests that IL-6 plays an important role in the development of high symptom burden during the initial month after stem cell transplant (4, 13, 19, 20). A cluster of symptoms (fatigue, disturbed sleep, lack of appetite, pain, and drowsiness) was consistently the most severe among all MDASI-MM symptoms assessed from day 18 to day þ100 of AuSCT. Methodologically, our longitudinal study was sufficiently powered to use mixed-effects modeling to detect the temporal association between symptom scores and expression of inflammatory markers, while controlling for confounding variables (17, 21 23). A high-dose melphalan conditioning regimen triggers a severe drop in WBC count and a resulting deficiency that could lead to infectious complications. This, along with residual disease, psychologic distress, and prolonged side effects from induction therapy, could contribute to inflammatory and symptom responses. Regardless of the Figure 3. Waterfall plot of the changes from baseline to nadir on the five most severe MDASI-MM symptoms and serum IL-6 concentrations. Change in IL-6 (ng/ml) OF6 Clin Cancer Res; 2014 Clinical Cancer Research

7 Inflammation and Symptoms in Autologous Stem Cell Transplant Table 4. Mixed-effects modeling: univariate and multivariate analysis of associations between changes in serum inflammatory markers and changes in severity of the five most severe symptoms from day 18 pre- AuSCT to day þ30 after AuSCT (natural log scale) Univariate models (327 observations) a Multivariate models (310 observations) b Marker Estimate c SE Pr > t Marker Estimate SE Pr > t Pain stnf-r stnf-r IL IL IL CRP Fatigue sil-1r sil-6r < sil-6r IL IL CRP Baseline mood score Disturbed sleep MIP-1a MIP-1a Lack of appetite CRP IL sil-6r Drowsiness IL IL sil-6r Baseline mood score Top five most severe symptoms IL < IL MIP-1a MIP-1a sil-6r sil-1r IL CRP Baseline mood score a For univariate models, each model presents the significance of the single inflammatory marker associated with the symptom outcome, as well as the estimate value, adjusted for quadratic time, age, gender, staging, BMI, baseline mood score, stem cell dose, and bortezomib-based induction regimen. b For multivariate models, each model presents the significance of inflammatory markers associated with the symptom outcome, as well as the estimate value, adjusted for other inflammatory markers from univariate analysis, quadratic time, age, gender, staging, BMI, baseline mood score, stem cell dose, and bortezomib-based induction regimen. The significant level of each model was set as 0.05/n (n, number of cytokines included in the model). c The estimate is a parameter estimated for a predictor. For natural log-transformed independent variables, the estimate shows how the outcome changes when the predictor changes by any ratio. For example, the estimate of natural log IL-6 levels for the mean severity of the top five symptoms was 0.196, which meant that when the level of IL-6 doubled (or increased 100%), there was a corresponding ln(2) ¼ 0.14-unit increase in the mean symptom score. effect of these factors, patients collectively shared not only the same severe symptoms, but also a similar symptom trajectory that was at its worst at WBC nadir after AuSCT. There was no significant change over time in pain severity, but because pain was persistently severe compared with other symptoms, we included it in the symptom component score. The univariate analysis identified that serum IL-6, sil-6r, IL-10, CRP, MIP-1a, sil-1r2, and stnf-r1 was significantly related to development of the five most severe symptoms during the same period. In examining the timing of peak or nadir of inflammatory marker expression compared with the peak in symptom burden at day þ8 during WBC nadir (range, day 4 10), we observed the closest correlations for Clin Cancer Res; 2014 OF7

8 Wang et al. IL-6 (positively) and IL-6R and MIP-1a (inversely). IL-6 has been identified as a primary marker associated with symptom-burden peak in both AuSCT and AlloSCT, which suggests that its role is more relevant to the nadir effect caused by treatment than to disease during the critical first month posttransplant, although IL-6 is a well-known disease growth factor in multiple myeloma (24). In view of the low WBC count, it is possible that the immune system is not the source of IL-6; IL-6 might alternatively be produced by other organ cells such as hepatocytes or endothelial cells. sil-1ra had an earlier nadir (day þ5) than the symptom peak and a more rapid decline than IL-6, indicating a more sensitive response to the transplant. To our knowledge, our study is the first to identify inverse associations between sil-6r and IL-6 and between sil-6r and fatigue severity. sil6r is known to increase IL-6 induced signaling by forming a complex with IL-6 and gp130 on the membranes of cells. The decrease in the level of sil-6r may protect the individual from even more proinflammatory signaling and subsequent development of more severe symptoms. How circulating cytokines signal the brain to trigger multiple severe symptoms in humans is unknown, although in animal studies it has been demonstrated that systemic cytokine production can influence behavior by inducing symptoms of sickness and depression (5, 25). Further, we cannot explain why levels of either TNF-a or its receptors were unchanged at the time point of chemotherapy-induced WBC nadir. Given that the peak response of CRP and IL-10 occurred after the symptom peak, these mediators are unlikely to initiate the development of severe symptoms (26). The study has several limitations. We designed our study to coincide with patients routine blood-draw schedules, so as to reduce the likelihood of missing data. Therefore, the timing of blood draws during the day may not have been consistently optimal and could have been affected by circadian patterns of cytokine release. Also, we collected a limited number of samples (totaling approximately 15% of all samples) during the day þ30 to þ100 period, due to fewer regularly scheduled follow-up visits during this time period. Finally, samples were kept for 2 to 4 hours at room temperature but were not tested for stability thereafter; this approach should be examined in future studies, as many cytokines are unstable. Additional studies might also examine observer-rated transplant-associated toxicities to gain a better understanding of such toxicities and symptom burden. In summary, defining the temporal development of inflammatory activity in concert with the development of high symptom burden is another step toward establishing a better understanding of the nature of treatment-induced symptom burden. Anti-inflammatory intervention may be further tested in clinical studies to establish the role of inflammation inhibition in relation to amelioration of severe symptoms, so long as this can be done without compromising the efficacy of the antitumor treatment. Reduction of therapy-associated symptoms should make cancer treatment more tolerable and therefore more accessible to those patients who might not otherwise be considered for aggressive cancer therapy. Disclosure of Potential Conflicts of Interest R.Z. Orlowski has received commercial research grants from Celgene, Bristol-Myers Squibb, Onyx Pharmaceuticals, and Millennium: The Takeda Oncology Company. He is also employed as a consultant/advisory board member with Celgene, Onyx Pharmaceuticals, Millennium: The Takeda Oncology Company, and Bristol-Myers Squibb. No potential conflicts of interest were disclosed by the other authors. Disclaimer Neither the National Cancer Institute (NCI) nor the NIH had any role in the study design, data collection, analysis, interpretation, or preparation of the report. Authors' Contributions Conception and design: X.S. Wang, J.M. Reuben, R.Z. Orlowski, L.A. Williams, C.S. Cleeland Development of methodology: X.S. Wang, J.M. Reuben, T.R. Mendoza, C. S. Cleeland Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): E.N. Cohen, J.M. Reuben, R.Z. Orlowski, M.H. Qazilbash, L.A. Williams, C.S. Cleeland Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): X.S. Wang, Q. Shi, N.D. Shah, C.J. Heijnen, J.M. Reuben, M.H. Qazilbash, V.E. Johnson, T.R. Mendoza Writing, review, and/or revision of the manuscript: X.S. Wang, Q. Shi, N. D. Shah, C.J. Heijnen, J.M. Reuben, R.Z. Orlowski, M.H. Qazilbash, L.A. Williams, T.R. Mendoza, C.S. Cleeland Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): J.M. Reuben Study supervision: X.S. Wang, L.A. Williams Acknowledgments The authors thank the editorial assistance of Jeanie F. Woodruff, BS, ELS, and data collection and management from Venus M. Ilagan, BA, CCRP, Jackie Joy, Brooke White, Gary M. Mobley, BS, MA, and Mary H. Sailors, PhD. Grant Support This study was supported by grants from the NCI of the NIH, including NCI P01 CA (to C.S. Cleeland) and MD Anderson Cancer Center Support Grant NCI P30 CA The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact. Received September 6, 2013; revised December 13, 2013; accepted December 18, 2013; published OnlineFirst January 14, References 1. Kyle RA, Rajkumar SV. Treatment of multiple myeloma: a comprehensive review. Clin Lymphoma Myeloma 2009;9: Anderson KO, Giralt SA, Mendoza TR, Brown JO, Neumann JL, Mobley GM, et al. Symptom burden in patients undergoing autologous stem-cell transplantation. Bone Marrow Transplant 2007;39: Wang XS, Shi Q, Williams LA, Cleeland CS, Mobley GM, Reuben JM, et al. Serum interleukin-6 predicts the development of multiple OF8 Clin Cancer Res; 2014 Clinical Cancer Research

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10 Inflammatory Markers and Development of Symptom Burden in Patients with Multiple Myeloma during Autologous Stem Cell Transplantation Xin Shelley Wang, Qiuling Shi, Nina D. Shah, et al. Clin Cancer Res Published OnlineFirst January 14, Updated version Access the most recent version of this article at: doi: / ccr alerts Sign up to receive free -alerts related to this article or journal. Reprints and Subscriptions Permissions To order reprints of this article or to subscribe to the journal, contact the AACR Publications Department at To request permission to re-use all or part of this article, use this link Click on "Request Permissions" which will take you to the Copyright Clearance Center's. (CCC) Rightslink site.