Partnering With Patients to Rapidly Develop a Quality-of-Life Measure in Mycosis Fungoides/Sézary Syndrome Type Cutaneous T-cell Lymphoma

Published on: 
, , ,
Evidence-Based Oncology, June 2016, Volume 22, Issue SP8

The field of measurement in Mycosis Fungoides/Sézary syndrome type cutaneous T-cell lymphoma lacked a specific quality-of-life measure to describe patient experience or guide treatment decisions. Using an online platform with an engaged patient community, we developed and psychometrically validated a new measure in just under a year.

Mycosis fungoides and its leukemic variant Sézary syndrome (MF/SS), comprise the most common forms of cutaneous T-cell lymphoma (CTCL), a class of Non-Hodgkin’s lymphomas.1 Approximately 3000 new cases of this rare disease are reported in the United States every year.1 While CTCL typically affects older adults (median age at diagnosis: 55 to 60 years2) around 7% of cases are diagnosed before age 30.3 CTCL also affects more males than females (male to female ratio is approximately 1.6:1) and is more prevalent within the black population (black-to-white ratio is approximately 1.3:1) although both these trends have been stabilizing relative to historic norms.4

Measuring the impact of MF/SS CTCL experience for research purposes, or even clinical management with a healthcare provider, is made more challenging by the absence of disease-specific validated measures.5 Clinicians currently use patient-reported outcome (PRO) tools such as the Itchy-QOL,6 DLQI,7 Skindex-29,8 VAS itch, or cancer PROs such as the EORTC family of tools9 or the FACT-G.10 In order to capture quality-of-life (QoL) information, both a cancer-specific (eg, FACT-G) and skin-specific (eg, Skindex-29) measures are often administered in trials, which is shown to be responsive to change, but, at 56 questions, these measures can be burdensome for patients.11

There is a dearth of literature on aspects of QoL impairment by specific MF/SS CTCL subgroups selected by gender, age, clinical type, treatment, or clinical status.12 Traditional clinical assessments (such as extent of lesion, lymph node involvement, or flow cytometry) do not capture patient perspective on how disease manifestation can have a major impact on many domains related to QoL,13 such as role function or psychological distress. As a result, there is little data on the relationship between MF/SS CTCL symptom burden and health-related QoL, and researchers have sought to answer whether the connotation of having a poorly understood form of cancer causes distress, over and above the consequences of cutaneous manifestations of disease.13

Addressing these gaps in the literature is challenging, because new condition-specific measures have traditionally been expensive and time consuming to develop. According to some estimates, the time taken may be as much as 2 to 4 years, and the costs range from $725,000 to $2.1 million, depending on the extent of rigor required for developing them.14,15 A robust research program requires:

  • A researcher trained in psychometrics
  • Ready access to a sizable sample of participants
  • Identification and licensing of relevant comparator measures
  • Staff to collect and analyze data
  • Longitudinal follow-up to determine minimally important differences
  • Efforts to disseminate the findings and support the instrument once released.

Even when resources are available, PROs, developed by researchers in isolation, risk measuring things that don’t really matter to patients.16 Despite the fact that the perspective of patients is increasingly recognized as crucial across many aspects of medical research,17 several legacy measures in widespread use today were developed with little or no patient input. These are significant challenges that are amplified when the condition of interest is as rare as MF/SS CTCL.


Early experiences have shown that patients using the internet to share information about their condition and to connect with peers can contribute their experiences to PRO developers in a rigorous fashion that helps overcome some of the aforementioned challenges.18-22 Methodology studies undertaken to evaluate the quality and representativeness of data gathered online has found that it is similar in nature to data gathered through more traditional means such as guided interview.23 Legitimate questions remain as to how online tools can verify patients identity, obtain objective data of their diagnosis and status, and overcome biases inherent in the use of online tools.24

Funded by a grant from the Robert Wood Johnson Foundation, PatientsLikeMe, built the Open Research Exchange (ORE),25 an online software platform with tools that simplify the process of developing, testing, and sharing new PROs. The instrument development process is based on a sequential multi-step, iterative process that complies with widely acceptable scientific recommendations 26-28 and FDA guidelines.29

The process consists of the following steps:

  1. Construct definition and conceptual framework
  2. Concept elicitation
  3. Feedback
  4. Psychometric evaluation
  5. Test-retest

ORE is connected to an online platform where more than 400,000 patients currently track their health, connect with others for information and support, and contribute data for research; consequently, the challenges of recruitment, data collection, and follow-up are rendered more manageable. To date, more than 20 new instruments have been developed using the platform, including published measures of treatment burden,30 extracampine hallucinations, in Parkinson’s disease,31 and hypertension.32

Recognizing the need for an MF-CTCL—specific HRQoL instrument, Actelion Pharmaceuticals, and PatientsLikeMe, sought to harness new technology to rapidly develop, prototype, and psychometrically validate a new instrument with patient input throughout. Our objective was to create an instrument that could be used to better understand patient unmet need (eg, disease burden, treatment satisfaction, and health-related QoL), and help characterize the experience of patients living with MF/SS CTCL. We also sought to contribute the tool to the wider community in a Creative Commons ShareAlike 3.0 license, so that it could be used, expanded upon, and improved by other researchers.

Developing the Instrument

While a full description of the study methods is beyond the scope of this article (for more, see Towers, et al33), we will summarize the approach taken. Following a literature review and interviews with clinical experts, 21 patients reporting a physician-confirmed diagnosis of MF/SS CTCL were invited to complete open-text concept elicitation items (eg, “How is your physical well-being affected by MF/SS CTCL?”). In addition, 10 patients out of the 21 were invited for further telephone interview to probe their answers. Qualitative analysis suggested that content saturation was reached after 15 patients and thematic content analysis identified 6 major themes that were subsequently used to generate a preliminary version of the 31-item questionnaire. This long-form questionnaire was administered to 42 patients for their item-level feedback, where multiple-choice and open text survey items allowed patients to identify issues with any items they found lacked clarity or relevance. After removing redundant items, an abbreviated 14-item scale was administered to a sample of 126 patients for psychometric validation, including comparator measures. Sixty-six patients completed test-retest performance, 5 days later, with known-group validity analysis.

Psychometric analysis showed good internal consistency, test-retest reliability, and that the items were appropriately ordered in terms of severity. We also found that the MF/SS CTCL QoL is capable of discriminating between individuals with low and high levels of interference in their QoL, and that the items adequately covered the varying levels of interference with QoL due to MF/SS CTCL. Further work detailing the validation process and final instrument is under preparation.


The use of the ORE platform enabled patient feedback to be easily incorporated throughout every step of the development process. Additionally, thanks in large part to a relationship with the Cutaneous Lymphoma Foundation, recruitment was faster and more cost effective than traditional methods of sourcing patients through clinical centers. Information collected from key opinion leaders and the literature helped to inform a scientifically grounded and relevant measure that accurately depicts the patient experience with MF/SS CTCL, particularly given the variability that patients often encounter, as they cope with the daily demands of the condition. Online feedback replaced more time and resource-expensive interviewer-led cognitive debriefing interviews. In all, the process took less than a year, and the total cost was a fraction of what traditional instrument development costs.


The greatest limitation of the study is the sample size, due in part to the rarity of the condition. A number of psychometric validation measures were, therefore, unable to be completed and could be addressed in future research. Additionally, while it is impossible to guarantee that those who registered on the website actually have MF/SS CTCL, a recent study in other conditions, on PatientsLikeMe, found that around 95% of patients could be identified via IMS Health medical and pharmacy claims (Eicher et al, In Press). Further, the sample of patients who participated in this study were largely in Stage 1 of mycosis fungoides, or Sézary syndrome, with few patients reporting more advanced stages of the syndrome (Stage III, n = 2; Stage IVa, n = 4; Stage IVb, n = 1). Inclusion of more individuals at later stages of the syndrome would allow for empirical testing of differential item function by later stages of the syndrome.



The MF/SS-CTCL PRO tool project represented a unique collaboration between a pharmaceutical company and a patient network, using an innovative platform to work on a new measure for a rare disease that would otherwise have never been developed. We hope use of the MF/SS CTCL-QoL tool, which is freely available, will enable better communications about QoL between patients and their care teams, and improve and inform clinical management and treatment decision making related to MF/SS-CTCL.

Author information

Paul Wicks, PhD, is vice president of innovation, PatientsLikeMe, Inc.

Marjan Sepassi, PharmD, is associate director, Medical Affairs, Actelion Pharmaceuticals, Inc.

Gaurav Sharma, PharmD, is associate director, Medical Affairs, Actelion Pharmaceuticals, Inc.

Margot Carlson Delogne, is vice president of communications, PatientsLikeMe, Inc.

Address for correspondence

Paul Wicks, PhD


160 2nd Street,

Cambridge, MA



  1. Jawed SI, Myskowski PL, Horwitz S, Moskowitz A, Querfeld C. Primary cutaneous T-cell lymphoma (mycosis fungoides and Sézary syndrome): part I. Diagnosis: clinical and histopathologic features and new molecular and biologic markers. J Am Acad Dermatol. 2014;70(2):205.e1—16. quiz 221-222. doi:10.1016/j.jaad.2013.07.049.
  2. Criscione VD, Weinstock MA. Incidence of cutaneous T-cell lymphoma in the United States, 1973-2002. Arch Dermatol. 2007;143(7):854-859. doi:10.1001/archderm.143.7.854.
  3. Weiyun A, Keegan T, Press D, et al. Outcomes After diagnosis of mycosis fungoides and Sézary Syndrome before 30 years of age. JAMA Dermatol. 2014;150(7):709-715. doi:10.1001/jamadermatol.2013.7747.
  4. Korgavkar, K, Xiong, M, Weinstock, M. Changing Incidence trends of cutaneous t-cell lymphoma. JAMA Dermatol. 2013;149(11):1295-1299. doi:10.1001/jamadermatol.2013.5526.
  5. Demierre MF, Kim YH, Zackheim HS. Prognosis, clinical outcomes and quality of life issues in cutaneous T-cell lymphoma. Hematol Oncol Clin North Am. 2003;17(6):1485-1507.
  6. Desai NS, Poindexter GB, Monthrope YM, Bendeck SE, Swerlick RA, Chen SC. A pilot quality-of-life instrument for pruritus. J Am Acad Dermatol. 2008;59(2):234-244. doi:10.1016/j.jaad.2008.04.006.
  7. Finlay AY, Khan GK. Dermatology Life Quality Index (DLQI) a simple practical measure for routine clinical use. Clin Exp Dermatol. 1994;19(3):210-216.
  8. Chren MM, Lasek RJ, Quinn LM, Mostow EN, Zyzanski SJ. Skindex, a quality-of-life measure for patients with skin disease: reliability, validity, and responsiveness. J Invest Dermatol. 1996;107(5):707-713.
  9. Aaronson NK, Ahmedzai S, Bergman B, et al. The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst. 1993;85(5):365-376.
  10. Cella DF, Tulsky DS, Gray G, et al. The Functional Assessment of Cancer Therapy scale: development and validation of the general measure. J Clin Oncol. 1993;11(3):570-579.
  11. Demierre MF, Ferzli P, Miller D. Measuring HRQOL in patients with cutaneous T-cell lymphoma undergoing therapy with oral bexarotene and extracorporeal photopheresis. Arch Dermatol. 2007;143(5):659-661. doi:10.1001/archderm.143.5.659.
  12. Sampogna F, Frontani M, Baliva G, et al. Quality of life and psychological distress in patients with cutaneous lymphoma. Br J Dermatol. 2009;160(4):815-822. doi:10.1111/j.1365-2133.2008.08992.x.
  13. Demierre M-F, Gan S, Jones J, Miller DR. Significant impact of cutaneous T-cell lymphoma on patients' quality of life: results of a 2005 National Cutaneous Lymphoma Foundation Survey. Cancer. 2006;107(10):2504-2511. doi:10.1002/cncr.22252.
  14. Rosen R. Development of Patient Reported Outcome (PRO) measures: how feasible is a PRO for asymptomatic PCa treatment? FDA website. Accessed May 3, 2016.
  15. Hayes R. Patient-Reported Outcome (PRO) Instruments as Drug Development Tools (Session III). In: Washington, DC; 2011. FDA website.
  16. Wicks P. Commentary: Measuring what matters: the case for patient generated PROMS. BMJ. 2015;350:h54. doi:10.1136/bmj.h54.
  17. de Wit M, Abma T, Loon MK-V, Collins S, Kirwan J. Involving patient research partners has a significant impact on outcomes research: a responsive evaluation of the international OMERACT conferences. BMJ Open. 2013;3(5):piie002241. doi:10.1136/bmjopen-2012-002241.
  18. Wicks P, Massagli MP, Wolf C, Heywood J. Measuring function in advanced ALS: validation of ALSFRS-EX extension items. Eur J Neurol. 2009;16(3):353-359. doi:10.1111/j.1468-1331.2008.02434.x.
  19. Wicks P, Vaughan TE, Massagli MP. The multiple sclerosis rating scale, revised (MSRS-R): development, refinement, and psychometric validation using an online community. Health Qual Life Outcomes. 2012;10:70. doi:10.1186/1477-7525-10-70.
  20. Bove R, Secor E, Healy BC, et al. Evaluation of an online platform for multiple sclerosis research: patient description, validation of severity scale, and exploration of BMI effects on disease course. Oreja-Guevara C, ed. PLoS ONE. 2013;8(3):e59707. doi:10.1371/journal.pone.0059707.
  21. Wicks P, Massagli M, Kulkarni A, Dastani H. Use of an online community to develop patient-reported outcome instruments: the Multiple Sclerosis Treatment Adherence Questionnaire (MS-TAQ). J Med Internet Res. 2011;13(1):e12. doi:10.2196/jmir.1687.
  22. Smith RA, Wicks P, Yagi N, Scheinker D, Thisted R. Development of a self report bulbar function scale. Neurology. March 2011:A48-A49. PatientsLikeMe website.
  23. McCarrier KP, Bull S, Fleming S, et al. Concept elicitation within patient-powered research networks: a feasibility study in chronic lymphocytic leukemia. Value Health. 2016;19(1):42-52. doi:10.1016/j.jval.2015.10.013.
  24. Rothman M, Gnanasakthy A, Wicks P, Papadopoulos EJ. Can we use social media to support content validity of patient reported outcome (PRO) instruments in Medical development? Value Health. 2015;18(1):1-4. doi:10.1016/j.jval.2014.10.001.
  25. Open Research Exchange website. Accessed May 2, 2016.
  26. Cappelleri JC, Zou KH, Bushmakin AG, Alvir JMJ, Alemayehu D, Symonds T. Patient-Reported Outcomes: Measurement, Implementation and Interpretation. Boca Raton, Fl: Chapman & Hall/CRC Press; 2013.
  27. DeVellis RF. Scale Development: Theory and Applications. 3rd ed: Vol 26. Thousand Oaks, CA: Sage Publishing; 2012.
  28. Kane RL, Radosevich DM. Conducting Health Outcomes Research. Sudbury, MA: Jones & Bartlett Learning; 2010.
  29. FDA. Guidance for industry. Patient-reported outcome measures: use in medical product development to support labeling claims. Federal Register. 2009;74(235):65132-65133.
  30. Tran VT, Harrington M, Montori VM, Barnes C, Wicks P, Ravaud P. Adaptation and validation of the Treatment Burden Questionnaire (TBQ) in English using an internet platform. BMC Med. 2014;12(1):109. doi:10.1186/1741-7015-12-109.
  31. Wood RA, Hopkins SA, Moodley KK, Chan D. Fifty percent prevalence of extracampine hallucinations in Parkinson’s disease patients. Front Neurol. 2015;6:263. doi:10.3389/fneur.2015.00263.
  32. Kear T, Harrington M, Bhattacharya A. Partnering with patients using social media to develop a hypertension management instrument. J Am Soc Hypertens. 2015;9(9):725-734. doi:10.1016/j.jash.2015.07.006.
  33. Towner A, Raja P, Braverman J, et al. Patients’ Experiences with mycosis fungoides/sézary syndrome-cutaneous t-cell lymphoma (Mf/Ss-Ctcl): evidence from qualitative research of a patient reported outcome (Pro) Measure developed on an online research platform.Value Health. 2015;18(3):A25. doi: