Possible Targets to Reduce Fatigue in Chronic Immune Thrombocytopenia Patients – An Explorative Study (2024)

Background Fatigue in immune thrombocytopenia (ITP) is frequent and burdensome, but we lack the knowledge to help these patients.

Aim The aim of the study is to explore the role of disease activity and other potentially modifiable factors in fatigue.

Method This cross-sectional study included adult chronic ITP patients (n = 59). Univariable linear regression (corrected for confounders) was used to determine the relationship between disease activity (platelet count <30 × 10⁹/L or treatment), disease-specific factors (bleeding symptoms, ferritin), and transdiagnostic factors (FACT-G physical/functional/emotional/social well-being subscales, physical activity level, and vitamin D) and fatigue (Checklist Individual Strength fatigue subscale). Several multivariable models with clustered sets of variables were used to compare the proportion of explained variance of fatigue (adjustedR²).

Results Significant relations with moderate effect sizes (>0.50) were found for physical and functional well-being and fatigue, and physical activity and fatigue. Other significant relations with fatigue (effect size 0.30–0.47) included skin and organ bleeding, emotional and social well-being, vitamin D, and disease activity. Notably, the models with disease activity and disease-specific factors explained <20% of the variance in fatigue, while the models with transdiagnostic factors (functioning and physical activity) explained >50%. Vitamin D alone explained 12% of the variance in fatigue.

Conclusion Transdiagnostic (non-disease-specific) rather than disease-specific factors explained a large part of the variance in ITP-related fatigue. Many factors related to fatigue are potentially modifiable and should be investigated as targets for interventions.

Subjects

The inclusion period ran from April 01, 2019 to July 01, 2021. We included patients with primary chronic ITP who had active disease at the time of study participation. Primary chronic ITP was defined according to the criteria of the American Society of Hematology: a current platelet count ≤100 × 10⁹/L, a disease duration of ≥1 year, and no indication of an underlying condition.²⁴Furthermore, patients with a current platelet count >100 × 10⁹/L because of current ITP treatment were also included, as they were also considered to have active disease. Patients were eligible if they were in care of the outpatient clinic of our tertiary center in the past or at the time of study participation, were ≥16 years of age, and willing and able to both understand the study information and give written informed consent. No additional exclusion criteria were applied.

Measurements

Demographics and disease specifics were extracted from the patient's medical record, and included age, sex, disease duration, comorbidities, and current ITP treatment.

The outcome, fatigue, was assessed by the fatigue severity subscale of the Checklist Individual Strength (CIS-fatigue). The CIS-fatigue is a self-reported questionnaire about the prior 14 days, that comprises eight items with a 7-point Likert scale scoring.²⁵²⁶²⁷The score ranges from 8 to 56. A cut-off score of 35 or more is used to define severe fatigue.²⁷The CIS-fatigue has been extensively validated in many chronically ill populations.¹⁵²⁸²⁹Recently, we have validated the CIS-fatigue in ITP.²³

To assess the role of disease activity, we categorized patients into high and low disease activity.⁴⁸³⁰In the high disease activity group, we aimed to include patients with a more active autoimmune reaction. Therefore, this group included both patients with a platelet count <30 × 10⁹/L or ITP therapy at the time of study participation. The low disease activity group included patients with a platelet count ≥30 × 10⁹/L without treatment.

We assessed several potentially modifiable factors. The assessed disease-specific factors were ferritin and bleeding symptoms measured by the ITP-Bleeding Assessment Tool (ITP-BAT).³¹³²Hemoglobin was not assessed as a potentially modifiable factor, because none of the patients in our sample were anemic. The ITP-BAT is a questionnaire that comprises several items regarding specific bleeding symptoms and is scored by a physician or trained researcher. It generates three separate scores, one for the skin domain (four items, e.g., petechiae, hematomas), one for the mucosal domain (five items, e.g., epistaxis, gum bleeding), and one for the organ domain (nine items, e.g., menorrhagia, gastrointestinal bleeding, hemoptysis). The highest item score within each domain reflects the final score for the respective domain. Each item is scored on severity, based on the worst incident in the prior 2 weeks. The severity score ranges from zero (not at all severe) to three or four (most severe) depending on the potential severity of the symptom. The non-disease-specific factors we assessed included level of physical activity, physical, functional, social, and emotional well-being, and vitamin D. The level of physical activity was measured by a subscale of the CIS, with three items on a 7-point Likert scale and a score range of 3 to 21; a higher score indicates more complaints.²⁵²⁶²⁷Similar to the CIS-fatigue, this subscale has been validated in the current study population.²³Functioning was measured with the Functional Assessment of Cancer Therapy-General (FACT-G), which is a questionnaire from the Functional Assessment of Chronic Illness Therapy (FACIT) measures.³³Although originally developed for patients with cancer, the scale has been used and validated in many other chronically ill populations, including human immunodeficiency virus and multiple sclerosis, as well as the healthy population.³³It comprises 27 items on quality of life that are divided into four subscales: physical well-being, functional well-being, social well-being, and emotional well-being. The five response options range from “Not at all” to “Very much.” Vitamin D was assessed by the 25-OH-vitamin D levels, using a routine laboratory test.

Statistical Analysis

Descriptive statistics were used to summarize the patient characteristics.

All subsequent analyses were done by linear regression. Each of the presented models were corrected for confounders, i.e., non-modifiable factors that are known to be related to fatigue: age, sex, the presence of comorbidity (dichotomous), and ITP duration in years.⁴⁸The assumptions of all linear regression models were tested for linearity between the dependent and independent variable, hom*oscedasticity, and normality of the residuals. Multicollinearity among the dependent variables and confounders in each model (defined as correlations stronger than 0.7) were ruled out. We did not strictly adhere to the rule of thumb of a maximum of one predictor per ten patients, as this study was primarily aimed to generate hypotheses.

First, the relationship between disease activity and fatigue was assessed. Second, separate models were made for each potentially modifiable factor, with the respective factor as the predictor and fatigue severity as the dependent variable. To compare the effects of the different models the effect sizes (standardized β's) were reported. An effect size of ≥|0.2|, ≥|0.5|, and ≥|0.8| was considered small, moderate, and large, respectively. For simplicity, we will refer to these models as univariable, even though they are corrected for confounders. Finally, we assessed how much of the variance of fatigue was explained by different sets of the factors. For this, we made several multivariable models with clustered sets of factors, i.e., one model with disease activity variable(s), one model with variables of the signs and symptoms of ITP, one model with the functioning variables, one model with physical activity level, and one model with vitamin D, respectively. The proportion of the variance of fatigue that was explained by each model was expressed by the adjustedR².

We performed two sensitivity analyses. The first assessed the relationship between the specific FACT-G items and fatigue. This was done by four multivariable models, one for each of the four subscales, where every model contained the items of the respective subscale as separate variables. This way, we were able to assess the contribution of the specific items to fatigue to further explore specific potential targets for intervention. The second analysis assessed the relative contribution of each significant (p<0,20) predictor if they are all combined into one multivariable model. Because our sample size is much too small for a model with so many predictors, it should be interpreted with caution, therefore we do not reportp-values for this analysis.

For the analyses with the FACT-G, two questions were removed from the original questionnaire: “I have a lack of energy” was removed from the physical well-being subscale because of its close resemblance to the outcome, fatigue; and “I am content with the quality of my life right now” from the functional well-being subscale because a reduced quality of life is a known consequence from fatigue that does not directly offer any potential for intervention. We do report the analyses using the full FACT-G scales (without removal of questions) inSupplementary Table S1.

Software

All analyses were performed in RStudio, version 2021.09.0 + 351.

Sample Size

We aimed at a sample size of 60 patients, which makes the study sufficiently powered to detect correlations of ≥0.355 (α = 0.05,β = 0.20), and thus assess internal consistency and convergent validity.

Table 1

Disease Activity and Fatigue

Severe fatigue was present in 16/34 (47%) patients with low disease activity and 17/25 (68%) patients with high disease activity. In the patients with high disease activity, severe fatigue occurred in 9/13 (69%) with a platelet count of ≥30 × 10⁹/L and treatment, and 8/12 (67%) with a platelet count of <30 × 10⁹/L.

Linear regression showed that patients with high disease activity were significantly more fatigued (Table 2, β 8.83,p = 0.02, ES 0.30). When we split the high disease activity group into patients with a platelet count of ≥30 × 10⁹/L and treatment and patients with a platelet count of <30 × 10⁹/L, both groups were still more fatigued than patients with low disease activity, although the confidence interval was too wide to reach statistical significance in the latter group (β 7.29, 95% CI −2.18 to 16.76, and β 10.72, 95% CI 0.47–20.97, respectively).

Potentially Modifiable Factors

Sensitivity Analysis: Exploring the Specific FACT-G Items

In the analysis assessing which specific items of each FACT-G subscale were related to fatigue, we found significant relationships for the patients' ability to meet the needs of the family (β −7,48,p<0.01, ES −0,62), sadness (β −7.33,p<0.01, ES −0.56), receiving emotional support from the family (β −7.99,p = 0.04, ES −0.48), the ability to work (β −5.58,p<0.01, ES −0.42), the quality of sleep (β −3.94,p = 0.01, ES −0.29), and the satisfaction with their sex life (β −4.76,p = 0.03, ES −0.38) (Supplementary Table S3).

The analysis that combined all significant predictors into one model showed that the level of physical activity and physical well-being remained the most relevant (ES >0.20). The effect sizes of the other well-being subscales, disease activity, vitamin D, and bleeding scores dropped below 0.20 (Supplementary Table S4).

Strengths and Weaknesses

This is the first study to explicitly search for transdiagnostic and potentially modifiable factors in ITP-related fatigue and to assess how much variance is explained by different sets of factors. This study design ensured clinical relevance by indicating which research direction is promising to help fatigued patients. The most important weakness of the study is the relatively small sample size, which makes this study primarily explorative and not fit for drawing firm conclusions. Furthermore, this study has partly taken place during the SARS-CoV-2 pandemic. This may have influenced our study results to some extent, particularly because the pandemic may have contributed to fatigue through personal or societal (transdiagnostic) factors. However, none of our patients had SARS-CoV-2-related complaints during study participation. Overall, we believe that the results are largely generalizable, although future research should confirm this. The other weaknesses of this study are due to its cross-sectional nature. First, there may be an overrepresentation of patients with a long duration of fatigue; the results may therefore mainly apply to patients with chronic fatigue. Furthermore, the causality of the factors that were related to fatigue cannot be demonstrated. However, fatigue is often not solely a cause or consequence. Instead, fatigue often has bi-directional interactions with factors such as depression, anxiety, social support, and ability to work.³⁴Previous research shows that interventions targeting such factors successfully reduced fatigue in other chronic diseases.^2235363738The last limitation of this study is the, intentional, lack of correction for multiple testing. We found this strategy appropriate, as the aim of this study was to explore plausible hypotheses rather than prove significance. The findings of this study should be confirmed in larger studies.

Fatigue and Transdiagnostic Factors

We found that all transdiagnostic factors were significantly related to fatigue and explained by far the largest part of the variance. This is supported by the full multivariable model where only transdiagnostic factors kept a relevant effect size. This is not surprising, as previous research also found that the specific diagnosis or disease-specific factors were only accountable for a small part of the variance in fatigue.^815161718Indeed, all identified factors in our study are well-known in the pathogenesis of fatigue in other chronic diseases.¹⁵Many have also been identified before in ITP-related fatigue, including vitality, social functioning, and emotional functioning.³⁴⁹Furthermore, anxiety and depressive symptoms are known to be frequently present in ITP and related to quality of life, although the relation with fatigue has not been directly assessed in ITP patients before.^39404142

Transdiagnostic factors offer potential targets for interventions. Although causality between transdiagnostic factors and fatigue could not be demonstrated in this study, fatigue is often perpetuated by a complex interplay of bidirectional relationships between different factors, as shown by the biopsychological model and the International Classification of Functioning, Disability and Health (ICF-model) from the World Health Organization.¹⁶⁴³Targeting one of the factors involved can improve the entire interplay, which can result in less fatigue. A good example is physical activity: a reduced activity is a normal response to short-term fatigue, but in the long term it may actually perpetuate fatigue by causing sleep disturbances and dysregulation of the sleep–wake cycle. Specific transdiagnostic factors that could be targeted with, for example, behavioral interventions could be sleep disturbances, physical inactivity, or experiencing a lack of emotional support from others. Indeed, behavioral interventions (e.g., cognitive-behavioral therapy, exercise therapy, and self-management programs) were all effective in reducing fatigue in several other chronic diseases.^2235363738Two specific findings were the quality of sleep, that was also associated with ITP-related fatigue in our sensitivity analysis, and the relative importance of vitamin D in explaining variance in fatigue. Sleep disturbances may be caused by a delayed melatonin secretion onset, in which case supplementation of melatonin may be effective. In other chronic diseases, melatonin supplementation was found to effectively reduce fatigue, although not in all trials.⁴⁴⁴⁵⁴⁶It may be worthwhile to explore this therapeutic option further. Vitamin D deficiency was highly prevalent in our study population (49%). Interestingly, reduced vitamin D levels have been found previously in ITP, as well as in other autoimmune cytopenias, and systemic lupus erythematosus (SLE), among others.⁴⁷⁴⁸⁴⁹In fact, vitamin D supplementation was found to reduce fatigue in (juvenile-onset) SLE.⁵⁰Although vitamin D supplementation in deficit patients will not solve all fatigue, further investigating the effect of this easy and cheap treatment option may also be worthwhile.

Of note, the specific factors playing a role may be very different between individuals, which urges for an individualized approach in management decisions. Overall, however, our study suggests that interventions regarding sleep, social, and emotional functioning, mood, and physical activity may successfully reduce fatigue in ITP.

Fatigue and Signs and Symptoms of ITP

We found that skin and organ bleeding were related to fatigue. Previous literature shows that bleeding symptoms are related to a lower quality of life and possibly fatigue, partly due to worries about physical appearance and suspicions about domestic abuse.^4783941Of note, high organ bleeding scores comprised mainly patients with menorrhagia, which is known to independently affect the quality of life in many different domains.⁵¹⁵²Bleeding symptoms may be a relevant target for interventions in fatigued patients. Depending on the type of bleeding, symptoms may be targeted symptomatically (for example with tranexamic acid or hormonal therapy in case of menorrhagia) or by increasing the platelet count with ITP-specific treatments. However, the benefits of ITP-specific treatment may not outweigh the side effects, particularly in patients with a platelet count ≥30 × 10⁹/L. It may therefore be interesting to study whether it is preferable to target cognitions regarding bleeding rather than the bleeding symptoms themselves. Importantly, signs and symptoms seem to explain only a limited part of the variance in fatigue. Resolution of bleeding symptoms is, therefore, unlikely to completely resolve fatigue.

Fatigue and Disease Activity

We found more fatigue in patients with high disease activity. The high disease activity group comprised both patients with a current platelet count below 30 × 10⁹/L and patients with current treatment. In both these subgroups, we assume that the fatigue is due to high disease activity. However, of course, both platelet count and treatment have their limitations as a proxy for disease activity. Instead, fatigue may be related to the thrombocytopenia in the first group and to treatment side effects in the second group.⁴⁸⁵³Unfortunately, we cannot distinguish between disease activity, thrombocytopenia, and treatment side effects in our study. It would, therefore, be insightful to use inflammation parameters in future research to measure the relation between fatigue and disease activity.⁸This has not been done before in ITP. The overall literature is ambiguous about the relationship between both platelet count and ITP-treatment and fatigue. For example, one previous study confirmed an independent association between a platelet count below 30 × 10⁹/L and fatigue,⁴but other studies contradicted it.³⁰⁵⁴This is in line with our results, as disease activity did explain a small part of the variance in fatigue, but other factors seem to play a more important role. Similarly, some studies found that ITP-treatment reduced fatigue, while others found no beneficial effect.⁶⁷⁸⁹Of course, our definition of low and high disease activity is somewhat arbitrary. More specific subgroups, such as patients with no response, partial response, and complete response with medication and without medication could provide additional information on the role of disease activity. Unfortunately, our sample size is too small for so many subgroups. However, it is important to realize that the disease activity accounted for only a limited part of the variance in fatigue. This is also illustrated by the presence of severe fatigue in patients with low disease activity, in both our study and other chronic diseases.¹³¹⁴¹⁷Possibly, inflammation is mainly involved in the initial phase of fatigue, while transdiagnostic factors, such as cognition and activity, play a larger role in the perpetuation of fatigue.²⁴⁸⁹More research is necessary to identify the different processes that lead to the occurrence and perpetuation of fatigue in ITP. However, based on this study, transdiagnostic symptoms seem a more promising target for ameliorating fatigue than disease activity.

Implications for Clinicians and Future Research

Clinicians may want to realize that disease activity, signs, and symptoms only partly explain fatigue. Treating the ITP will, thus, often not solve the fatigue. Although this study is only explorative, it may be advised to address transdiagnostic factors in the doctor's office, for example by providing adequate verbal and written information and discussing topics such as anxiety, fear, physical activity, and the acceptance of family and friends. Furthermore, this study generated many promising hypotheses: including the potential benefit of interventions targeting psychosocial factors, physical activity, quality of sleep, and vitamin D levels. Further research should investigate whether modifying these factors will indeed reduce ITP-related fatigue. Specific interventions that could be further explored are self-management programs, exercise therapy, cognitive behavioral therapy, and/or vitamin D supplementation. Furthermore, further research should explore a more personalized approach, so that counselling and interventions can be tailored to the individual.

Conflict of Interest None declared.

Additional supporting information can be found online in the Supporting Information section at the end of the article.

Supplementary Tables

•Supplementary Table S1. All models assessing the relation between complete (without removal of questions) physical and functional well-being subscale and fatigue

•Supplementary Table S2. Immune thrombocytopenia Bleeding Assessment Tool (ITP-BAT) scores per domain and item in all patients

•Supplementary Table S3. Multivariable models assessing the relative contribution of the questions within the respective subscales of the Functional Assessment of Cancer Therapy-General (FACT-G)

•Supplementary Table S4. Full model with all significant predictors (p<0.20)

The research was designed and performed by W.E.M.v.D. and REGS. The analyses were performed by W.E.M.v.D. W.E.M.v.D. wrote the manuscript, which was critically revised by M.M.N.V., H.K., and R.E.G.S..

What Is Known on This Topic?

• Fatigue is considered one of the top symptoms that patients with immune thrombocytopenia would like to have resolved.

• In many other chronic diseases, disease activity or the specific diagnosis only explains the variance in fatigue for a small part.

What Does This Paper Add?

• This hypothesis generating study suggests that fatigue in chronic immune thrombocytopenia is only partly explained by disease activity, but for a much larger part by transdiagnostic factors.

• Transdiagnostic factors that were associated with fatigue included physical and functional well-being, activity, and vitamin D.

1. Al-Samkari H, Kuter D J. Immune thrombocytopenia in adults: modern approaches to diagnosis and treatment. Semin Thromb Hemost. 2020;46(03):275–288. [PubMed] [Google Scholar]

2. Cooper N, Kruse A, Kruse C. Immune thrombocytopenia (ITP) World Impact Survey (iWISh): patient and physician perceptions of diagnosis, signs and symptoms, and treatment. Am J Hematol. 2021;96(02):188–198. [PMC free article] [PubMed] [Google Scholar]

3. Efficace F, Mandelli F, Fazi P. Health-related quality of life and burden of fatigue in patients with primary immune thrombocytopenia by phase of disease. Am J Hematol. 2016;91(10):995–1001. [PubMed] [Google Scholar]

4. Newton J L, Reese J A, Watson S I. Fatigue in adult patients with primary immune thrombocytopenia. Eur J Haematol. 2011;86(05):420–429. [PubMed] [Google Scholar]

5. White M H, Bennett C M. Fatigue is common in paediatric immune thrombocytopenia and improves with second-line treatments. Br J Haematol. 2020;191(01):15–16. [PubMed] [Google Scholar]

6. Kuter D J, Rummel M, Boccia R. Romiplostim or standard of care in patients with immune thrombocytopenia. N Engl J Med. 2010;363(20):1889–1899. [PubMed] [Google Scholar]

7. Cheng G, Saleh M N, Marcher C.Eltrombopag for management of chronic immune thrombocytopenia (RAISE): a 6-month, randomised, phase 3 study Lancet 2011377(9763):393–402. [PubMed] [Google Scholar]

8. Hill Q A, Newland A C. Fatigue in immune thrombocytopenia. Br J Haematol. 2015;170(02):141–149. [PubMed] [Google Scholar]

9. Grace R F, Klaassen R J, Shimano K A. Fatigue in children and adolescents with immune thrombocytopenia. Br J Haematol. 2020;191(01):98–106. [PubMed] [Google Scholar]

10. George J N, Mathias S D, Go R S. Improved quality of life for romiplostim-treated patients with chronic immune thrombocytopenic purpura: results from two randomized, placebo-controlled trials. Br J Haematol. 2009;144(03):409–415. [PubMed] [Google Scholar]

11. Kuter D J, Mathias S D, Rummel M. Health-related quality of life in nonsplenectomized immune thrombocytopenia patients receiving romiplostim or medical standard of care. Am J Hematol. 2012;87(05):558–561. [PubMed] [Google Scholar]

12. Gudbrandsdottir S, Birgens H S, Frederiksen H. Rituximab and dexamethasone vs dexamethasone monotherapy in newly diagnosed patients with primary immune thrombocytopenia. Blood. 2013;121(11):1976–1981. [PubMed] [Google Scholar]

13. Van Dijk-Lokkart E M, Steur L MH, Braam K I. Longitudinal development of cancer-related fatigue and physical activity in childhood cancer patients. Pediatr Blood Cancer. 2019;66(12):e27949. [PubMed] [Google Scholar]

14. Menting J, Nikolaus S, van der Veld W M, Goedendorp M M, Tack C J, Knoop H. Severe fatigue in type 1 diabetes: Exploring its course, predictors and relationship with HbA_1cin a prospective study. Diabetes Res Clin Pract. 2016;121:127–134. [PubMed] [Google Scholar]

15. Menting J, Tack C J, Bleijenberg G. Is fatigue a disease-specific or generic symptom in chronic medical conditions? Health Psychol. 2018;37(06):530–543. [PubMed] [Google Scholar]

16. World Health Organization . WHO; 2001. The International Classification of Functioning, Disability and Health (ICF) [Google Scholar]

17. Nap-van der Vlist M M, Dalmeijer G W, Grootenhuis M A. Fatigue among children with a chronic disease: a cross-sectional study. BMJ Paediatr Open. 2021;5(01):e000958. [PMC free article] [PubMed] [Google Scholar]

18. Stein R EK, Jessop D J. What diagnosis does not tell: the case for a noncategorical approach to chronic illness in childhood. Soc Sci Med. 1989;29(06):769–778. [PubMed] [Google Scholar]

19. Society of Gynecologic Surgeons Systematic Review Group . Matteson K A, Rahn D D, Wheeler T L., II Nonsurgical management of heavy menstrual bleeding: a systematic review. Obstet Gynecol. 2013;121(03):632–643. [PMC free article] [PubMed] [Google Scholar]

20. Menting J, Tack C J, Donders R, Knoop H. Potential mechanisms involved in the effect of cognitive behavioral therapy on fatigue severity in Type 1 diabetes. J Consult Clin Psychol. 2018;86(04):330–340. [PubMed] [Google Scholar]

21. TREFAMS-ACE Study Group . van den Akker L E, Beckerman H, Collette E H. Cognitive behavioral therapy positively affects fatigue in patients with multiple sclerosis: results of a randomized controlled trial. Mult Scler. 2017;23(11):1542–1553. [PubMed] [Google Scholar]

22. Menting J, Tack C J, van Bon A C. Web-based cognitive behavioural therapy blended with face-to-face sessions for chronic fatigue in type 1 diabetes: a multicentre randomised controlled trial. Lancet Diabetes Endocrinol. 2017;5(06):448–456. [PubMed] [Google Scholar]

23. van Dijk W EM, Penson A, Kuijlaars I AR. Checklist individual strength to measure severe fatigue in immune thrombocytopenia. Br J Haematol. 2022;197(03):e41–e44. [PubMed] [Google Scholar]

24. Provan D, Stasi R, Newland A C. International consensus report on the investigation and management of primary immune thrombocytopenia. Blood. 2010;115(02):168–186. [PubMed] [Google Scholar]

25. Vercoulen J H, Alberts M, Bleijenberg G. De Checklist Individual Strength (CIS) Gedragstherapie. 1999;32:131–136. [Google Scholar]

26. Vercoulen J HMM, Swanink C MA, Fennis J FM, Galama J MD, van der Meer J WM, Bleijenberg G. Dimensional assessment of chronic fatigue syndrome. J Psychosom Res. 1994;38(05):383–392. [PubMed] [Google Scholar]

27. Worm-Smeitink M, Gielissen M, Bloot L. The assessment of fatigue: psychometric qualities and norms for the Checklist individual strength. J Psychosom Res. 2017;98:40–46. [PubMed] [Google Scholar]

28. Dittner A J, Wessely S C, Brown R G. The assessment of fatigue: a practical guide for clinicians and researchers. J Psychosom Res. 2004;56(02):157–170. [PubMed] [Google Scholar]

29. Hewlett S, Dures E, Almeida C. Measures of fatigue: Bristol Rheumatoid Arthritis Fatigue Multi-Dimensional Questionnaire (BRAF MDQ), Bristol Rheumatoid Arthritis Fatigue Numerical Rating Scales (BRAF NRS) for severity, effect, and coping, Chalder Fatigue Questionnaire (CFQ), Checklist Individual Strength (CIS20R and CIS8R), Fatigue Severity Scale (FSS), Functional Assessment Chronic Illness Therapy (Fatigue) (FACIT-F), Multi-Dimensional Assessment of Fatigue (MAF), Multi-Dimensional Fatigue Inventory (MFI), Pediatric Quality Of Life (PedsQL) Multi-Dimensional Fatigue Scale, Profile of Fatigue (ProF), Short Form 36 Vitality Subscale (SF-36 VT), and Visual Analog Scales (VAS) Arthritis Care Res (Hoboken) 2011;63 11:S263–S286. [PubMed] [Google Scholar]

30. Zhou Z, Yang L, Chen Z. Health-related quality of life measured by the Short Form 36 in immune thrombocytopenic purpura: a cross-sectional survey in China. Eur J Haematol. 2007;78(06):518–523. [PubMed] [Google Scholar]

31. Rodeghiero F, Michel M, Gernsheimer T. Standardization of bleeding assessment in immune thrombocytopenia: report from the International Working Group. Blood. 2013;121(14):2596–2606. [PubMed] [Google Scholar]

32. Kumar M, Dutta S, Bhattyacharyya M. Application of ITP-BAT bleeding score in clinical practice. Int J Hematol. 2015;101(02):207–208. [PubMed] [Google Scholar]

33. Webster K, Cella D, Yost K. The Functional Assessment of Chronic Illness Therapy (FACIT) Measurement System: properties, applications, and interpretation. Health Qual Life Outcomes. 2003;1(01):79. [PMC free article] [PubMed] [Google Scholar]

34. Hewlett S, Chalder T, Choy E. Fatigue in rheumatoid arthritis: time for a conceptual model. Rheumatology (Oxford) 2011;50(06):1004–1006. [PubMed] [Google Scholar]

35. Evers A WM, Kraaimaat F W, van Riel P LCM, de Jong A JL.Tailored cognitive-behavioral therapy in early rheumatoid arthritis for patients at risk: a randomized controlled trial Pain 2002100(1-2):141–153. [PubMed] [Google Scholar]

36. van Kessel K, Moss-Morris R, Willoughby E, Chalder T, Johnson M H, Robinson E. A randomized controlled trial of cognitive behavior therapy for multiple sclerosis fatigue. Psychosom Med. 2008;70(02):205–213. [PubMed] [Google Scholar]

37. Franek J. Self-management support interventions for persons with chronic disease: an evidence-based analysis. Ont Health Technol Assess Ser. 2013;13(09):1–60. [PMC free article] [PubMed] [Google Scholar]

38. Vazgiourakis V M, Zervou M I, Eliopoulos E. Implication of VEGFR2 in systemic lupus erythematosus: a combined genetic and structural biological approach. Clin Exp Rheumatol. 2013;31(01):97–102. [PubMed] [Google Scholar]

39. Mathias S D, Gao S K, Miller K L. Impact of chronic Immune Thrombocytopenic Purpura (ITP) on health-related quality of life: a conceptual model starting with the patient perspective. Health Qual Life Outcomes. 2008;6(01):13. [PMC free article] [PubMed] [Google Scholar]

40. Tsukune Y, Komatsu N. Management of adult chronic immune thrombocytopenia in Japan: patient and hematologist perspectives from a multi-center cross-sectional questionnaire survey. Intern Med. 2016;55(17):2379–2385. [PubMed] [Google Scholar]

41. Suvajdzic N, Zivkovic R, Djunic I. Health-related quality of life in adult patients with chronic immune thrombocytopenia in Serbia. Platelets. 2014;25(06):467–469. [PubMed] [Google Scholar]

42. Trotter P, Hill Q A. Immune thrombocytopenia: improving quality of life and patient outcomes. Patient Relat Outcome Meas. 2018;9:369–384. [PMC free article] [PubMed] [Google Scholar]

43. Engel G L.The need for a new medical model: a challenge for biomedicine. Science 1977196(4286):129–136. [PubMed] [Google Scholar]

44. van Heukelom R O, Prins J B, Smits M G, Bleijenberg G. Influence of melatonin on fatigue severity in patients with chronic fatigue syndrome and late melatonin secretion. Eur J Neurol. 2006;13(01):55–60. [PubMed] [Google Scholar]

45. Castro-Marrero J, Zaragozá M C, López-Vílchez I. Effect of melatonin plus zinc supplementation on fatigue perception in myalgic encephalomyelitis/chronic fatigue syndrome: a randomized, double-blind, placebo-controlled trial. Antioxidants. 2021;10(07):1010. [PMC free article] [PubMed] [Google Scholar]

46. Lund Rasmussen C, Klee Olsen M, Thit Johnsen A. Effects of melatonin on physical fatigue and other symptoms in patients with advanced cancer receiving palliative care: a double-blind placebo-controlled crossover trial. Cancer. 2015;121(20):3727–3736. [PubMed] [Google Scholar]

47. Nguyen M H, Bryant K, O'Neill S G. Vitamin D in SLE: a role in pathogenesis and fatigue? A review of the literature. Lupus. 2018;27(13):2003–2011. [PubMed] [Google Scholar]

48. Lassandro G, Carriero F, Palmieri V. Serum vitamin D levels in children with immune thrombocytopenia. Endocr Metab Immune Disord Drug Targets. 2020;20(02):221–226. [PubMed] [Google Scholar]

49. Fattizzo B, Zaninoni A, Bianchi P, Fermo E, Nesa F, Barcellini W.25-OH vitamin D, vitamin D receptor and immunomodulatory cytokines serum levels in patients with autoimmune citopenias: correlation with hematologic parameters and clinical severityBlood 2014;124(21):

50. Zheng R, Gonzalez A, Yue J. Efficacy and safety of vitamin D supplementation in patients with systemic lupus erythematosus: a meta-analysis of randomized controlled trials. Am J Med Sci. 2019;358(02):104–114. [PubMed] [Google Scholar]

51. Liu Z, Doan Q V, Blumenthal P, Dubois R W. A systematic review evaluating health-related quality of life, work impairment, and health-care costs and utilization in abnormal uterine bleeding. Value Health. 2007;10(03):183–194. [PubMed] [Google Scholar]

52. Shankar M, Chi C, Kadir R A. Review of quality of life: menorrhagia in women with or without inherited bleeding disorders. Haemophilia. 2008;14(01):15–20. [PubMed] [Google Scholar]

53. Berti D, Moons P, Dobbels F, Deuson R, Janssens A, De Geest S. Impact of corticosteroid-related symptoms in patients with immune thrombocytopenic purpura: results of a survey of 985 patients. Clin Ther. 2008;30(08):1540–1552. [PubMed] [Google Scholar]

54. Sarpatwari A, Watson S, Erqou S. Health-related lifestyle in adults and children with primary immune thrombocytopenia (ITP) Br J Haematol. 2010;151(02):189–191. [PubMed] [Google Scholar]