Original Article

# Long-Term Fatigue in Survivors of Non-Hodgkin Lymphoma:
The Lymphoma Study Association SIMONAL
Cross-Sectional Study

Nicolas Mounier, MD¹; Sabine Anthony, PhD²; Raphaël Busson, PhD³,⁴; Catherine Thieblemont, MD⁵;
Vincent Ribrag, MD⁶; Hervé Tilly, MD⁷; Corinne Haioun, MD⁸; René-Olivier Casasnovas, MD⁹;
Franck Morschhauser, MD¹⁰; Pierre Feugier, MD¹¹; Richard Delarue, MD¹²; Loïc Ysebaert, MD
ID ¹³;
Catherine Sebban, MD¹⁴; Florence Broussais-Guillaumot, MD¹⁵; Gandhi Damaj, MD¹⁶; Virginie Nerich, PharmD
ID ¹⁷;
Jean-Philippe Jais, MD¹⁸; Lilian Laborde, BSc¹⁹; Gilles Salles, MD²⁰,²¹; and Michel Henry-Amar, MD
ID ⁴

**BACKGROUND:** Long-term survivors of non-Hodgkin lymphoma (NHL) must cope with treatment complications and late toxicities that affect their health-related quality of life. Little is known about the risk-to-benefit ratio of new agents like rituximab. The impact of treatment regimens and health disorders on long-term fatigue levels was investigated in a cross-sectional study. **METHODS:** Two self-administered questionnaires, the 20-item Multidimensional Fatigue Inventory (MFI-20) and a Life Situation Questionnaire, were mailed in 2015 to NHL survivors enrolled onto 12 successive clinical studies (1993-2010) conducted by the Lymphoma Study Association. Private addresses were obtained for 3317 survivors, of whom 1671 (50%) returned the questionnaires. Severe fatigue was defined as MFI-20 scores ≥60 on dimension scales scored from 0 to 100. Linear regression models were used to assess factors that were linked to increased fatigue levels. **RESULTS:** The study population included 906 men and 765 women, and the median age was 64 years (age range, 24-95 years). Overall, 811 survivors had received cyclophosphamide, doxorubicin, vincristine, prednisone (CHOP)-like chemotherapy, 518 had received high-dose CHOP, and 342 had undergone upfront autologous stem cell transplantation; 829 survivors also had received rituximab. In total, 1100 survivors (66%) reported 1 or more late health disorders. Severe fatigue was reported by 602 survivors (37%). Increased fatigue levels were associated (P < .001) with increased age, obesity, and the presence of health disorders, but not with initial treatment or rituximab. **CONCLUSIONS:** The survey confirms that high proportions long-term NHL survivors have severe fatigue. The results suggest that initial treatment and the receipt of rituximab have no influence on the development of long-term fatigue. **Cancer 2019;125:2291-2299. © 2019 American Cancer Society.**

**KEYWORDS:** cross-sectional study, long-term fatigue, long-term survivors, non-Hodgkin lymphomas, risk factors.

## INTRODUCTION

During the last 2 decades, the clinical outcome of patients with non-Hodgkin lymphoma (NHL) has improved dramatically because of the availability of new treatment options, such as noncytotoxic drugs that specifically target disease

**Corresponding author:** Michel Henry-Amar, MD, Centre de Traitement des Données du Cancéropôle Nord-Ouest, Plateforme de Recherche Clinique Ligue Contre le Cancer, Centre François Baclesse, 3 Avenue Général Harris, 14076 Caen Cedex 05, France; m.henry.amar@baclesse.unicancer.fr

¹Onco-Hematology Unit, l'Archet Hospital, Nice University Hospital Center, University of Côte d'Azur, Nice, France; ²Clinical Research and Innovation Office, Cimiez Hospital, Nice University Hospital Center, University of Côte d'Azur, Nice, France; ³Mathematics, Information, and Engineering Systems (MIIS) Doctoral School, Caen-Normandy University, Caen, France; ⁴French Center on eHealth, North-West Region Data Processing Center and French National League Against Cancer Clinical Research Platform, Caen, France; ⁵Hemato-Oncology Unit, Saint-Louis University Hospital Center, Public Hospital Network of Paris, Paris, France; ⁶Hematology Unit, Gustave Roussy Cancer Campus, Villejuif, France; ⁷Hematology Department and French Institute of Health and Medical Research (INSERM) Unit 1243, Henri Becquerel Center, Rouen, France; ⁸Lymphoid Malignancies Unit, Henri Mondor University Hospital Center, Public Hospital Network of Paris, Créteil, France; ⁹Hematology Unit and French Institute of Health and Medical Research (INSERM) Unit 1231, Bocage Hospital, Dijon Bourgogne Regional University Hospital Center, Dijon, France; ¹⁰Hematology Transfusion Institute, Claude Huriez Hospital, Lille Regional University Hospital Center, Lille, France; ¹¹Hematology Unit, Brabois Hospital, Nancy University Hospital Center, Vandœuvre-lès-Nancy, France; ¹²Hematology Unit, Necker University Hospital for Sick Children, Public Hospital Network of Paris, Paris, France; ¹³Oncopole, Toulouse University Cancer Institute, Toulouse, France; ¹⁴Hematology Unit, Léon Bérard Center, Lyon, France; ¹⁵Clinical Research Department-Lymphoma Study Association, Lyon South Hospital Center, Pierre-Bénite, France; ¹⁶Basse-Normandy Hematology Institute, Côte de Nacre Regional University Hospital Center, Caen, France; ¹⁷Regional Federative Institute of Cancerology, Besançon, France; ¹⁸Laboratory of Biostatistics, Paris V University-Descartes, Paris, France; ¹⁹Paoli-Calamettes Institute-Provence-Alpes-Côte d'Azur (IPC-PAPA) Data Processing Center, Marseille, France; ²⁰Faculty of Medicine, Claude Bernard University, Lyon, France; ²¹Hematology Department, Lyon South Hospital Center, Pierre-Bénite, France.

This work was presented in part at the 52nd Annual Meeting of the American Society of Clinical Oncology; June 4-7, 2016, Chicago, Illinois; and at the 43rd Annual Meeting of the European Society for Blood and Marrow Transplantation; March 26-29, 2017; Marseille, France.

We are grateful to all survivors who participated in the survey. We gratefully acknowledge Pierre Hebel and Vanina Oliveri from the Clinical Research and Innovation Office, Nice University Hospital Center, for their involvement in logistic and administration of the survey; Frederick Christy and Pauline Pontois from the Data Processing Center, Paoli-Calamettes Institute-Provence-Alpes-Côte d'Azur (IPC-PAPA), Marseille, for data entry; and Gilles Girault, scientific librarian at the Francois Baclesse Center, for his valuable help in publication retrieval.

Additional supporting information may be found in the online version of this article.

**DOI:** 10.1002/cncr.32040 **Received:** September 3, 2018; **Revised:** February 6, 2019; **Accepted:** February 6, 2019, **Published online** March 22, 2019 in Wiley Online Library (wileyonlinelibrary.com)
mechanisms.¹ The efficacy of rituximab and the lack of its cross-resistance with chemotherapy make it an attractive candidate for incorporation into existing chemotherapy regimens, including high-dose intensification and autologous stem cell transplantation (ASCT).²,³

Lymphoma survivors often have to cope with late toxicities and long-term fatigue, a symptom that approximately 30% of cancer survivors of any type endure for various lengths of time after treatment.⁴ With increasing remission rates and survival length, the assessment of long-term health status has become a key issue in judging the patients' therapeutic benefit. To our knowledge, no detailed assessments of long-term health disorders, fatigue, and rehabilitation to normal life during the postrituximab follow-up period have been performed to date.

The Lymphoma Study Association (LYSA) is an international network of more than 100 cooperating centers that are world pioneers in NHL treatment with novel agents or intensification strategies. Since the first trial initiation in 1987, almost 10,000 patients have been enrolled in LYSA studies. Data from these unique studies offer the opportunity to assess long-term health disorders and fatigue up to 20 years after diagnosis in real-life situations while controlling for histologic type, clinical characteristics, and initial therapy.

In a cross-sectional study, we investigated the health status of survivors who had a median follow-up of 11 years (range, 5-22 years) after initial treatment of their lymphoma. Special attention was paid to long-term fatigue and its correlations with initial treatment strategies and health disorders.

## MATERIALS AND METHODS

To be eligible, survivors had to live in France in 2015 and to have at least 5 years of follow-up since treatment initiation. From 1993 to 2010, 8113 patients with newly diagnosed, histologically confirmed, CD20-positive, diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), or T-cell lymphoma were enrolled onto 12 LYSA studies (Supporting Table 1; for participating centers, see Supporting Materials). Sociodemographic, clinical, and treatment characteristics and follow-up data were collected prospectively and stored in a secured database at the LYSA Academic Research Organization (Lyon South Hospital Center, Pierre-Bénite, France).

### Population Study

Of the 8113 patients who were registered, 5937 were alive at their last examination, of whom 4361 were French survivors living in France in 2015; they formed

the target population (Fig. 1). Of these 4361 survivors, 1044 were excluded for various reasons: 224 had less than 5 years of follow-up, 5 had left France, 28 had incomplete administrative records, and 787 were being followed at hospitals that were not willing to participate in the study. Overall, 3317 long-term survivors according to the Surbone and Tralongo definition⁵ were eligible for the survey.

### Questionnaires

Two self-administered questionnaires were used. The nonvalidated Life Situation Questionnaire (LSQ) addresses issues not available in other validated questionnaires, including the following sections: sociodemographic data, including marital status and highest level of education⁶; parenthood data; education, work, and insurance; health situation, including height, weight, and detailed information on immediate post-treatment fatigue (within 3 years), post-treatment health disorders, and current treatments; and social situation.⁷,⁸ The LSQ used targeted inquires to collect information. The weight (kg)-to-height (m)² ratio was used to calculate the body mass index (BMI) at the time of survivorship assessment; obesity was defined as a BMI ≥30 kg/m². The validated, 20-item Multidimensional Fatigue Inventory (MFI-20) was used to address the topic of cancer-related fatigue.⁹ It covers 5 dimensions of fatigue: general fatigue, physical fatigue, mental fatigue, reduced motivation, and reduced activity. Each dimension scale ranges from 0 to 100, and a high score indicates a high level of fatigue. Fatigue levels were defined based on analyses performed on a random sample of a European general population considering the distribution of the MFI-20 general fatigue dimension score (coded from 4 to 20): no fatigue (<75th percentile), moderate fatigue (75th to 89th percentile), and severe fatigue (90th to 100th percentile).¹⁰ By using linear transformation to fit our data, a score between 40 and 59 corresponded to moderate general fatigue, and scores ≥60 corresponded to severe general fatigue. In the current study, a score ≥40 for a given dimension was considered abnormal, and individuals who had all scores <40 were counted as having no fatigue.

### Clinical Data

Information on baseline patient characteristics and primary treatments received was obtained from the LYSA database. Chemotherapy was categorized into conventional or intensive.¹¹ Conventional chemotherapy was used in 10 studies, and intensive chemotherapy (mainly high-dose cyclophosphamide, doxorubicin, vincristine,
<figure><img src="image_1.png" /><figcaption>**Figure 1.** This is a flow chart of the Signal Detection in Monoclonal and New Agents in Lymphoma (SIMONAL) study. Information on vital status was obtained from the French Epidemiological Center on the Medical Causes of Death-French Institute of Health and Medical Research (available at: http://www.cepidc.inserm.fr/; accessed January 29, 2019). LYSA indicates Lymphoma Study Association.</figcaption></figure>

prednisone [CHOP] or CHOP-like regimens, such as doxorubicin [Adriamycin], cyclophosphamide, vindesine, bleomycin, prednisone [ACVBP]) was used in 8 studies, of which 6 also proposed ASCT (Supporting Table 1). In 8 studies, patients received upfront rituximab chemotherapy. Consolidation radiotherapy on residual masses was used only in LNH-93 study. For patients who progressed or had a relapse, no detailed information was computerized other than the date the event occurred. Most of these patients received second-line intensive chemotherapy and underwent ASCT. Self-reported health disorders that occurred at least 6 months after the end of lymphoma treatment were categorized as follows: second cancer; oral, cardiovascular, pulmonary, digestive, and musculoskeletal disorders; severe infections; anxiety; depression; and miscellaneous.

## Statistical Analyses

To study whether the characteristics of participants and nonparticipants were similar, demographic data, treatment protocols, medical history, acute treatment toxicity, relapse, and follow-up duration were compared using appropriate statistical tests. Follow-up was calculated from the date of treatment initiation to the date of survey participation. Health disorders were summarized in the 10 classes listed above. Results correspond to the proportion of participants who reported at least 1 of these health disorders since their lymphoma treatment. The distributions of the fatigue scores were compared with those of a random sample of a European general population adjusted on the distribution of age and sex in that population, which were the only available detailed data published.¹² Comparisons were made using *t* tests. Multivariate linear
regression models were used to assess factors that were
linked to an increased fatigue level at time of the survey.
The explanatory variables tested were: age, sex, education
level (elementary school, middle school, high school, or
university), relationship with partner (no or yes), obesity
(BMI $\ge$30 kg/m$^2$ in 2015; no or yes), histologic type
(DLBCL, T-cell, or FL), treatment intensity (conven-
tional or intensive chemotherapy), radiation therapy (no
or yes), targeted therapy (rituximab or others), ASCT (no
or yes), acute grade 3/4 toxicity (no or yes), fatigue within
3 years after treatment (no or yes), and relapse (no or yes).
Health disorders other than NHL that developed after
treatment for NHL was completed also were included
in the models. A backward elimination procedure was
used to remove nonsignificant correlations with an
exclusion criterion of $P$ > .05 on 15-fold cross-validation.
Treatment with rituximab (yes or no) was forced in all
models. In multivariate linear models, the intercept rep-
resents the reference score. Here, it corresponded to the
predicted score for a man aged 20 years with a university
education who had received no radiotherapy or rituximab,
expressed no fatigue after treatment, was not in relation-
ship with a partner at the time of survivorship assessment,
was not obese, and was without any history of health dis-
orders. For a different profile, the predicted score was ob-
tained by adding the $\beta$ coefficients of the characteristics
to the intercept. Ninety-five percent confidence intervals
(95% CIs) of predicted scores were calculated using the
bootstrap method.¹³ Statistical tests were 2-sided, and sta-
tistical significance was defined as a $P$ < .05. All analyses
were performed using the SAS statistical software package
(version 9.3; SAS Institute, Cary, NC).

Regulatory Compliance

This study was approved by the French legal authori-
ties (the Consultative Committee for Data Processing in
Health Research [Comité Consultatif pour le Traitement
de l'Information dans le domaine de la Recherche en
Santé (CCTIRS)] and the National Commission on
Informatics and Liberty [Commission Nationale de
l'Informatique et des Libertés (CNIL)]; no. DR-204-252).

RESULTS

After approval by the ethical committee and French
legal authorities, the 2 questionnaires were mailed in
May 2015 to the 3317 survivors who were eligible for
the survey. After sending a reminder 6 months later, in
total, 1671 survivors (50.4%) survivors had participated.
Details of the logistic aspects of the study and the meth-
odology used have been published.¹⁴

Comparison Between Participants
and Nonparticipants

Participants and nonparticipants did not differ on
demographic characteristics (Table 1). Patients who had
enrolled on more recent trials (starting in 2000 and be-
yond) and those who had benefited from intensive or
maintenance therapy or had received targeted therapy
were more likely to participate. These differences led
to shorter follow-up among participants, and they also
more often developed grade 3/4 toxicity during initial
treatment.

Participant Characteristics

Of the 1671 participants, the ratio of men to women
was 1.18. Histologic types were DLBCL in 1176 survi-
vors (70%), FL in 472 survivors (28%), and T-cell lym-
phoma in 23 survivors (2%). At the time of diagnosis,
1321 participants (79%) were aged $\le$60 years. The mean
age (± standard deviation) decreased with increasing
educational level: it was 72.5 ± 7.9 years for those with an
elementary school education, 65.3 ± 10.5 years for those
with a middle school education, 60.0 ± 11.7 years for
those with a high school education, and 57.7 ± 14.0 years
for those with a university level education. Conventional
chemotherapy had been received by 811 participants
(49%), intensive chemotherapy had been received by
518 (31%), and intensive chemotherapy plus ASCT had
been received by 342 (20%). Overall, 829 participants
(50%) had received rituximab chemotherapy, 346 (21%)
had undergone ASCT, and 84 (5%) had received con-
solidation radiotherapy (Table 1). In total, 292 partici-
pants (17%) reported immediate fatigue after treatment.
Follow-up ranged from 5 to 9 years in 527 participants
(32%), from 10 to 14 years in 570 participants (34%),
and from 15 to 22 years in 574 participants (34%).

Long-Term Fatigue

At the time of survivorship assessment, of the 1619 par-
ticipants who completed the fatigue assessment form,
1036 individuals (64%; 95% CI, 62%-66%) expressed
at least 1 fatigue score $\ge$40. Of these, 434 individuals
(27%; 95% CI, 25%-29%) had moderate fatigue, and
602 (37%; 95% CI, 35%-40%) had severe fatigue. In
contrast, 583 individuals (36%) reported no fatigue
(Supporting Table 2). Women reported severe fatigue
more often than men, including general fatigue (32% vs
23%; *P* < .001), physical fatigue (26% vs 18%; *P* = .001),
and reduced motivation (14% vs 8%; *P* < .001). The pro-
portion of participants reporting severe fatigue also was
correlated with obesity at 37% versus 25%, respectively
<table><caption>**TABLE 1.** The Signal Detection in Monoclonal and New Agents in Lymphoma (SIMONAL) Study: Demographic and Upfront Treatment Characteristics by Status in Participants Versus Nonparticipants</caption><thead><tr><th rowspan="2">Characteristic</th><th colspan="2">No. (%)</th><th rowspan="2">P</th></tr><tr><th>Nonparticipants, N = 1646</th><th>Participants, N = 1671</th></tr></thead><tbody><tr><td>Age: Median [range], y</td><td></td><td></td><td></td></tr><tr><td>Actual age</td><td>64 [25-101]</td><td>64 [24-95]</td><td>.02</td></tr><tr><td>Age at randomization</td><td>51 [16-87]</td><td>51 [16-87]</td><td>.34</td></tr><tr><td>Sex</td><td></td><td></td><td>.31</td></tr><tr><td>Men</td><td>863 (52)</td><td>906 (54)</td><td></td></tr><tr><td>Women</td><td>783 (48)</td><td>765 (46)</td><td></td></tr><tr><td>Histologic type</td><td></td><td></td><td>&lt;.001</td></tr><tr><td>Diffuse large B-cell</td><td>1295 (79)</td><td>1176 (70)</td><td></td></tr><tr><td>Follicular</td><td>323 (19)</td><td>472 (28)</td><td></td></tr><tr><td>T-cell</td><td>28 (2)</td><td>23 (2)</td><td></td></tr><tr><td>Protocol<sup>a</sup></td><td></td><td></td><td>&lt;.001</td></tr><tr><td>LNH 93 (1993-2002)</td><td>621 (38)</td><td>390 (23)</td><td></td></tr><tr><td>GELF 94 (1994-2001)</td><td>78 (5)</td><td>93 (6)</td><td></td></tr><tr><td>LNH 98 (1999-2002)</td><td>250 (15)</td><td>234 (14)</td><td></td></tr><tr><td>FL2000 (2000-2002)</td><td>69 (4)</td><td>103 (6)</td><td></td></tr><tr><td>LNH 01 (2001-2005)</td><td>25 (1)</td><td>19 (1)</td><td></td></tr><tr><td>LNH 03 (2003-2009)</td><td>339 (21)</td><td>441 (26)</td><td></td></tr><tr><td>PRIMA (2004-2007)</td><td>159 (10)</td><td>265 (16)</td><td></td></tr><tr><td>RCHOP-Velcade (2005-2006)</td><td>17 (1)</td><td>11 (&lt;1)</td><td></td></tr><tr><td>RAIL (2005-2008)</td><td>4 (&lt;1)</td><td>3 (&lt;1)</td><td></td></tr><tr><td>LNH 05 (2006-2007)</td><td>10 (&lt;1)</td><td>11 (&lt;1)</td><td></td></tr><tr><td>ZBEAM2 (2007-2008)</td><td>17 (1)</td><td>30 (2)</td><td></td></tr><tr><td>LNH 07 (2007-2010)</td><td>57 (3)</td><td>71 (4)</td><td></td></tr><tr><td>Chemotherapy intensity<sup>b</sup></td><td></td><td></td><td>.01</td></tr><tr><td>Conventional chemotherapy</td><td>773 (47)</td><td>811 (49)</td><td></td></tr><tr><td>Intensive chemotherapy</td><td>584 (35)</td><td>518 (31)</td><td></td></tr><tr><td>Intensive chemotherapy + ASCT</td><td>289 (18)</td><td>342 (20)</td><td></td></tr><tr><td>Rituximab</td><td></td><td></td><td>.001</td></tr><tr><td>No</td><td>1023 (62)</td><td>842 (50)</td><td></td></tr><tr><td>Yes</td><td>623 (38)</td><td>829 (50)</td><td></td></tr><tr><td>Other targeted therapy</td><td></td><td></td><td>.01</td></tr><tr><td>No</td><td>1491 (91)</td><td>1468 (88)</td><td></td></tr><tr><td>Yes</td><td>155 (9)</td><td>203 (12)</td><td></td></tr><tr><td>Stem cell transplantation</td><td></td><td></td><td>.01</td></tr><tr><td>No</td><td>1364 (83)</td><td>1325 (79)</td><td></td></tr><tr><td>Yes</td><td>282 (17)</td><td>346 (21)</td><td></td></tr><tr><td>Radiotherapy</td><td></td><td></td><td>.001</td></tr><tr><td>No</td><td>1514 (92)</td><td>1587 (95)</td><td></td></tr><tr><td>Yes</td><td>132 (8)</td><td>84 (5)</td><td></td></tr><tr><td>Maintenance therapy<sup>c</sup></td><td></td><td></td><td>&lt;.001</td></tr><tr><td>No</td><td>1581 (96)</td><td>1548 (93)</td><td></td></tr><tr><td>Yes</td><td>65 (4)</td><td>123 (7)</td><td></td></tr><tr><td>Medical history<sup>d</sup></td><td></td><td></td><td>&lt;.001</td></tr><tr><td>No</td><td>856 (52)</td><td>768 (46)</td><td></td></tr><tr><td>Yes</td><td>790 (48)</td><td>903 (54)</td><td></td></tr><tr><td>Upfront grade 3/4 treatment-related toxicity</td><td></td><td></td><td>&lt;.001</td></tr><tr><td>No</td><td>1043 (63)</td><td>942 (56)</td><td></td></tr><tr><td>Yes</td><td>603 (37)</td><td>729 (44)</td><td></td></tr><tr><td>Relapse</td><td></td><td></td><td>.07</td></tr><tr><td>No</td><td>1395 (85)</td><td>1377 (82)</td><td></td></tr><tr><td>Yes</td><td>251 (15)</td><td>294 (18)</td><td></td></tr><tr><td>Follow-up duration, y</td><td></td><td></td><td>&lt;.001</td></tr><tr><td>Median [range]</td><td>14 [5-22]</td><td>11 [5-22]</td><td></td></tr><tr><td>5-9</td><td>380 (23)</td><td>527 (32)</td><td></td></tr><tr><td>10-14</td><td>465 (28)</td><td>570 (34)</td><td></td></tr><tr><td>15-22</td><td>801 (49)</td><td>574 (34)</td><td></td></tr></tbody></table>

Abbreviations: ASCT, autologous stem cell transplantation; FL2000, cyclophosphamide, doxorubicin, teniposide, and prednisone (CHVP)-interferon versus CHVP-interferon plus rituximab in follicular lymphoma; GELA, French Adult Lymphoma Study Group; LNH, GELA lymphoma trials; PRIMA, primary rituximab and maintenance; RAIL, rituximab combined with cyclophosphamide, doxorubicin, vincristine, and prednisone in T-cell angioimmunoblastic lymphoma; RCHOP-Velcade, rituximab combined with cyclophosphamide, doxorubicin, vincristine, and prednisone (RCHOP) with bortezomib; ZBEAM2, phase 2 trial of zevalin, carmustine, etoposide, aracytine, and melphalan.

<sup>a</sup>See Supporting Table 1.

<sup>b</sup>According to data from Zelenetz AD, Gordon LI, Wierda WG, et al; National Comprehensive Cancer Network. Non-Hodgkin's lymphomas, version 4.2014.

J Natl Compr Canc Netw. 2014;12:1282-1303.¹¹

<sup>c</sup>All patients who received maintenance therapy also received rituximab.

<sup>d</sup>These were health disorders other than non-Hodgkin lymphoma.
<figure><img src="image_2.png" /><figcaption>**Figure 2.** Scores are compared for different dimension scales on the 20-item Multidimensional Fatigue Inventory (MFI-20) (with 95% confidence intervals) from the Signal Detection in Monoclonal and New Agents in Lymphoma (SIMONAL) study in data from a European general population stratified for sex and age (see Schwarz R, Krauss O, Hinz A. Fatigue in the general population. *Onkologie*. 2003;26:140-144¹²). Asterisks denote *P* < .001. GFF indicates general fatigue; MFF, mental fatigue; NHL, non-Hodgkin lymphoma; PFF, physical fatigue; RAF, reduced activity; RMF, reduced motivation.</figcaption></figure>

(*P* < .001), for general fatigue, and 19% versus 13% (*P* = .014), respectively, for reduced activity in those with a BMI ≥30 kg/m² versus a BMI <30 kg/m², respectively. Severe fatigue was independent of histologic type, initial treatment intensity, radiation therapy, receipt of rituximab or ASCT, and relapse. Compared with data from general population, participants displayed significantly (*P* < .001) higher levels of fatigue for all dimensions except for reduced activity (Fig. 2).

Multivariate linear models were applied to the 5 dimensions of fatigue on the MFI-20 assessment tool, and results of the final models are provided in Table 2. In all models, rituximab was forced. Taking the reduced motivation dimension of fatigue as an example, characteristics that negatively influenced the predicted score were age at the time of survivorship assessment, self-reported fatigue after treatment, obesity, and (among health disorders) cardiovascular disorders or peripheral artery diseases and anxiety. In contrast, relationships with a partner positively influenced the level of reduced motivation. For this dimension of fatigue, the reference group consisted of participants aged 20 years, without a relationship with a partner, with no fatigue after treatment, a BMI <30 kg/m², and no health disorders; the corresponding reference score was 17.0 (equaling the intercept). For participants who have different characteristics, the reduced motivation score can be constructed

by adding significant terms. Changes according to various profiles are illustrated in Figure 3. Having at least 1 health disorder increased all scores.

Among sociodemographic characteristics, age influenced all dimensions, only being a woman influenced general fatigue, education level moderately influenced reduced activity and mental fatigue, and having a relationship with a partner positively influenced motivation and mental fatigue and reduced activity. Treatment intensity (including ASCT) as well as receipt of rituximab had no impact on any fatigue dimensions. In contrast, self-reported fatigue after treatment and obesity increased fatigue levels in all dimensions (except mental fatigue for obesity). Finally, cancer history had a limited impact on reduced activity only. Whatever the fatigue dimension, significant β coefficient values of any health disorders ranged from 2.8 to 13.4.

## DISCUSSION

To our knowledge, the current study is the first to report on long-term fatigue in a large sample of French NHL survivors taking into account patients' characteristics and health disorders. Individuals who were enrolled in clinical studies from 1993 to 2010 were asked to report on their health using self-administered questionnaires. Data collected by LYSA investigators on demographic, clinical, and treatment characteristics (chemotherapy regimens, radiation therapy, ASCT, rituximab, maintenance therapy, toxicity, and early relapse) were used to assess the potential role of treatment on long-term fatigue with no clinical update made at the time of survivorship assessment.

These results confirm the belief shared by most hematologists that NHL survivors have altered health status over time, with three-quarters of the study population reporting symptomatic fatigue. The reason why fatigue lasts so long after cancer treatment has been completed is unclear and probably multifactorial.¹⁵ Recommendations for fatigue screening are available from the American Society of Clinical Oncology and the National Comprehensive Cancer Network.⁴,¹⁶ Both groups recommend a quantitative or semiquantitative assessment, such as a numeric rating scale (eg, with scores from 0 to 10), allowing, for example, subgrouping into those with no fatigue (a score of 0), mild fatigue (scores of 1-3), moderate fatigue (scores of 4-6), and severe fatigue (scores of 7-10). Because fatigue is rarely an isolated symptom, multisymptom assessment tools like the MFI-20 questionnaire also are recommended.⁴ Studies that have
<table><caption>TABLE 2. Signal Detection in Monoclonal and New Agents in Lymphoma (SIMONAL) Study: Multiple Linear Regression Model on Multidimensional Fatigue Inventory Components of Long-Term Fatigueª</caption><thead><tr><th rowspan="2">Variable</th><th colspan="2">General Fatigue<br>(Adj R<sup>2</sup> = 22.9)</th><th colspan="2">Physical Fatigue<br>(Adj R<sup>2</sup> = 24.9)</th><th colspan="2">Reduced Activity<br>(Adj R<sup>2</sup> = 17.3)</th><th colspan="2">Reduced<br>Motivation<br>(Adj R<sup>2</sup> = 15.3)</th><th colspan="2">Mental Fatigue<br>(Adj R<sup>2</sup> = 12.2)</th></tr><tr><th>Coef β</th><th>P</th><th>Coef β</th><th>P</th><th>Coef β</th><th>P</th><th>Coef β</th><th>P</th><th>Coef β</th><th>P</th></tr></thead><tbody><tr><td>Intercept<sup>b</sup></td><td>31.8</td><td>&lt;.001</td><td>23.8</td><td>&lt;.001</td><td>10.5</td><td>&lt;.001</td><td>17.0</td><td>&lt;.001</td><td>23.6</td><td>&lt;.001</td></tr><tr><td>Age at time of survey by 10-y<br>increase</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>20-69 y</td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>4.4</td><td>&lt;.001</td><td>1.7</td><td>.004</td><td>NA</td><td>—</td></tr><tr><td>≥70 y</td><td>10.9</td><td>&lt;.001</td><td>13.4</td><td>&lt;.001</td><td>4.4</td><td>&lt;.001</td><td>11.6</td><td>&lt;.001</td><td>4.2</td><td>.006</td></tr><tr><td>Sex</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Men</td><td>Ref</td><td>—</td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>NA</td><td>—</td></tr><tr><td>Women</td><td>1.9</td><td>.002</td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>NA</td><td>—</td></tr><tr><td>Education level</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>University</td><td></td><td></td><td></td><td></td><td>Ref</td><td>—</td><td>NA</td><td>—</td><td>Ref</td><td>—</td></tr><tr><td>High school</td><td></td><td></td><td></td><td></td><td>0.9</td><td>.511</td><td></td><td></td><td>1.2</td><td>.435</td></tr><tr><td>Middle school</td><td></td><td></td><td></td><td></td><td>3.9</td><td>.020</td><td></td><td></td><td>3.8</td><td>.033</td></tr><tr><td>Elementary school</td><td></td><td></td><td></td><td></td><td>-0.2</td><td>.942</td><td></td><td></td><td>2.6</td><td>.169</td></tr><tr><td>Treatment using radiotherapy</td><td>NA</td><td></td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>-7.5</td><td>.009</td></tr><tr><td>Treatment using rituximab</td><td>-0.5</td><td>.684</td><td>0.8</td><td>.524</td><td>0.3</td><td>.822</td><td>-0.4</td><td>.710</td><td>-1.1</td><td>.393</td></tr><tr><td>Immediate fatigue after treatment<sup>c</sup></td><td>15.8</td><td>&lt;.001</td><td>16.6</td><td>&lt;.001</td><td>10.3</td><td>&lt;.001</td><td>8.3</td><td>&lt;.001</td><td>10.9</td><td>&lt;.001</td></tr><tr><td>Relationship with partner</td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>-3.5</td><td>.006</td><td>-4.6</td><td>&lt;.001</td><td>-3.7</td><td>.008</td></tr><tr><td>History of second cancer</td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>4.3</td><td>.041</td><td>NA</td><td>—</td><td>NA</td><td>—</td></tr><tr><td>Obesity at time of survey<sup>d</sup></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>BMI ≥30 kg/m<sup>2</sup></td><td>6.6</td><td>&lt;.001</td><td>7.6</td><td>&lt;.001</td><td>5.1</td><td>&lt;.001</td><td>5.0</td><td>&lt;.001</td><td>NA</td><td>—</td></tr><tr><td>Patient-reported health disorders</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Oral</td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>4.5</td><td>.003<sup>e</sup></td></tr><tr><td>Cardiovascular</td><td>4.7</td><td>.002<sup>f</sup></td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>2.8</td><td>.047<sup>f</sup></td><td>4.4</td><td>.004<sup>g</sup></td></tr><tr><td>Peripheral artery diseases</td><td>11.9</td><td>.014</td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>13.4</td><td>.002</td><td>NA</td><td>—</td></tr><tr><td>Cardiac arrhythmia</td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>8.0</td><td>&lt;.001</td><td>NA</td><td>—</td><td>NA</td><td>—</td></tr><tr><td>Pulmonary</td><td>9.4</td><td>&lt;.001<sup>h</sup></td><td>10.1</td><td>&lt;.001<sup>i</sup></td><td>8.8</td><td>&lt;.001<sup>i</sup></td><td>NA</td><td>—</td><td>NA</td><td>—</td></tr><tr><td>Severe infections</td><td>5.0</td><td>.006<sup>j</sup></td><td>4.7</td><td>.011<sup>j</sup></td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>NA</td><td>—</td></tr><tr><td>Musculoskeletal</td><td>9.6</td><td>&lt;.001<sup>k</sup></td><td>12.5</td><td>&lt;.001<sup>k</sup></td><td>6.1</td><td>&lt;.003<sup>k</sup></td><td>NA</td><td>—</td><td>NA</td><td>—</td></tr><tr><td>Anxiety</td><td>11.7</td><td>&lt;.001</td><td>10.4</td><td>&lt;.001</td><td>7.7</td><td>&lt;.001</td><td>12.2</td><td>&lt;.001</td><td>12.6</td><td>&lt;.001</td></tr><tr><td>Depression</td><td>4.8</td><td>.035</td><td>6.3</td><td>.008</td><td>NA</td><td>—</td><td>NA</td><td>—</td><td>NA</td><td>—</td></tr></tbody></table>

Abbreviations: Adj R², adjusted coefficient of determination based on results from the multivariate linear model; BMI, body mass index; Coef β, beta coefficient; MFI-20, 20-item Multidimensional Fatigue Inventory; NA, not applicable; Ref, reference category.

ªFor adjusted R² values, the higher the value, the better the model fits the distribution of observed values.

ᵇIntercept indicates the baseline score for an individual aged 20 years with no risk factors.

ᶜFatigue is reported within 3 years after the beginning of upfront treatment.

ᵈBMI is measured as weight (kg)/height (m²).

ᵉOral disorders include dental prosthesis, ageusia, very dry mouth, and tooth extraction-related complications.

ᵉCardiovascular disorders include heart failure, heart valvulopathies, cardiac arrhythmia, and thrombosis.

ᵉCardiovascular disorders include heart failure, heart valvulopathies, cardiac arrhythmia, stroke, thrombosis, and peripheral artery diseases.

ᵇPulmonary disorders include pleuritis and impaired pulmonary function.

¹Pulmonary disorders include pleuritis, impaired pulmonary function, and chronic obstructive pulmonary disease.

¹Severe infections include herpes zoster, hepatitis B, hepatitis C, and tuberculosis.

⁴Musculoskeletal disorders include avascular necrosis of bone, muscular fibrosis, and severe osteoarthritis.

reported on fatigue in the general population are limited, and only 1 of these used the MFI-20 questionnaire.¹²,¹⁷⁻¹⁹ In our study, the limits above which NHL survivors were considered to have severe fatigue corresponded to the 90th percentile of the distribution of any MFI-20 dimensions observed in a European general population.¹² According to the European Organization for Research and Treatment of Cancer Quality-of-Life Core questionnaire, the median fatigue score in the Dutch general population was between 11 and 20 on a scale from 0 to 100, and 4% of individuals had scores >60.¹⁸ Other authors have reported a

significant (*P* < .01) 60% increase in mean fatigue scores among adolescent and young adult lymphoma survivors (mean follow-up, 4.2 years; mean age at the time of survivorship assessment, 34.7 years) compared with the general population.²⁰ Although the results are not strictly comparable, the finding that 37% of adult NHL survivors had at least 1 fatigue score ≥60 suggests that long-term fatigue represents a serious complication in this population. Most published studies have focused on health-related quality of life using instruments that occasionally include item(s) on fatigue. Of these, only 1 studied chronic fatigue and
<figure><img src="image_3.png" /><figcaption>**Figure 3.** Changes in mean scores on the general fatigue (GFF) and reduced motivation (RMF) scales (with 95% confidence intervals) on the 20-item Multidimensional Fatigue Inventory (MFI-20) are illustrated for the Signal Detection in Monoclonal and New Agents in Lymphoma (SIMONAL) study using various profiles. The baseline profiles correspond to individuals aged 20 years living without a partner who have no fatigue after treatment, a body mass index (BMI) <30 kg/m² at the time of survivorship assessment, and no health disorders. In profile 1, in addition to baseline characteristics, individuals are aged 70 years; in profile 2, individuals are aged 70 years and present with a BMI ≥30 kg/m²; in profile 3, individuals are aged 70 years and present with a BMI ≥30 kg/m² and cardiovascular disorders; and, in profile 4, individuals are aged 70 years and present with a BMI ≥30 kg/m², cardiovascular disorders, and anxiety. Mean scores are derived from the data listed in Table 2. For example, the predicted RMF score for an individual aged 75 years who is living without a partner and has a BMI ≥30 kg/m² and no health disorders (profile 2 and age 75 years) = (intercept + β<sub>age &lt;70 years</sub> * [minimum (age, 70 years) - 20]/10 + β<sub>age ≥70 years</sub> * [maximum (age, 70 years) - 70]/10 + β<sub>BMI</sub>) = 17.0 + (1.7 × 5) + (11.6 × 0.5) + 5.0 = 36.3.</figcaption></figure>

its relation with hormone dysfunction as a result of treatment.²¹ In a series of 98 Norwegian NHL survivors who received radiotherapy to the head-and-neck region (median age, 61.3 years; median follow-up, 16.4 years), the authors observed that 29% of survivors expressed chronic fatigue based on the Fatigue Questionnaire (FQ) assessment, independent of sex, age, and treatment. In multivariate analysis, using the Hospital Anxiety and Depression questionnaire to assess anxiety or depression, chronic fatigue was dependent on anxiety/depression (*P* < .001) and on hormone dysfunction (*P* = .02), in agreement with our results. Similarly, in the current study, no correlations were observed between initial treatment type and long-term levels of fatigue, as previously reported among Hodgkin lymphoma survivors in 2 longitudinal studies.²²,²³

This study has certain limitations that could partially be overcome. It was a cross-sectional study that included no direct comparisons with data from the

French general population. However, fatigue levels could be compared with those in the European general population using data that were standardized on age and sex. Second, the participants represented 50.4% of the target population, which is lower than the proportions observed in surveys of the Dutch or Nordic general populations¹⁷,¹⁸ but similar to that reported in the European Organization for Research and Treatment of Cancer survey of Hodgkin lymphoma survivors.⁸ Third, the collected health data had no medical confirmation, and a memory bias cannot be excluded. Although targeted inquiries were used on the form, the possible bias probably concerns only health disorders that did not require permanent medication or that had no major impact on personal daily life.²⁴

In conclusion, the current study can be considered as a real-life picture of the health status of NHL survivors that can be used in decision making. The findings confirm that fatigue represents a major concern in long-term survivors of NHL. Our results suggest that long-term fatigue is independent of disease characteristics (including histologic type), initial treatment, as well as treatment for recurrent disease; whereas obesity and comorbidities play a role in the development of fatigue that persists or develops early after treatment completion. However, before various tertiary prevention interventions to manage or prevent the development of long-term fatigue are undertaken, the biologic origin of persistent fatigue should be questioned.

## FUNDING SUPPORT

This study was supported by a grant from the French drug regulatory agency (National Agency for the Safety of Medicines; AAP-2012-20). Raphaël Busson is the recipient of a fellowship from the French National League Against Cancer (2014-2016). Michel Henry-Amar is supported by the French National League Against Cancer.

## CONFLICTS OF INTEREST DISCLOSURES

The authors made no disclosures.

## AUTHOR CONTRIBUTIONS

**Nicolas Mounier:** Conception and design, data analysis and interpretation, writing, and approval of the final version. **Sabine Anthony:** Conception and design, collection and assembly of data, data analysis and interpretation, writing, and approval of the final version. **Raphaël Busson:** Data analysis and interpretation, writing, and approval of the final version. **Catherine Thieblemont:** Writing and approval of the final version. **Vincent Ribrag:** Writing and approval of the final version. **Hervé Tilly:** Writing and approval of the final version. **Corinne Haioun:** Writing and approval of the final version. **René-Olivier Casasnovas:** Writing and approval of the final version. **Franck Morschhauser:** Writing and approval of the final version. **Pierre Feugier:** Writing and approval of the final version. **Richard Delarue:** Writing and approval of the final version. **Loïc Ysebaert:** Writing and approval of the final version. **Catherine Sebban:** Writing and approval of the final version. **Florence Broussais-Guillaumot:** Collection and assembly of data, writing,
and approval of the final version. **Gandhi Damaj:** Writing and approval of the final version. **Virginia Nerich:** Conception and design, data analysis and interpretation, writing, and approval of the final version. **Jean-Philippe Jais:** Conception and design, data analysis and interpretation, writing, and approval of the final version. **Lilian Laborde:** Collection and assembly of data, writing, and approval of the final version. **Gilles Salles:** Writing and approval of the final version. **Michel Henry-Amar:** Conception and design, data analysis and interpretation, writing, and approval of the final version.

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