Supportive Care in Cancer

, Volume 27, Issue 2, pp 521–530 | Cite as

Development and prospective evaluation of CAPLET, a cancer ambulatory patient physical function longitudinal evaluation tool for routine clinical practice

  • Elizabeth Hall
  • Emily Tam
  • Mindy Liang
  • Quihuang Zhang
  • Lin Liu
  • Lauren Wong
  • Samantha Sarabia
  • Sabrina Yeung
  • Gursharan Gill
  • Lawson Eng
  • Andrea Perez-Cosio
  • M. Catherine Brown
  • Wei Xu
  • Madeline Li
  • Nicole Mittmann
  • Jennifer Jones
  • Doris HowellEmail author
  • Geoffrey LiuEmail author
Original Article



A patient’s physical function is a critical outcome variable for measuring and improving chronic care management. However, patient-reported outcome measures of physical function are not routinely assessed in cancer outpatients, in part due to limitations of tools available. This study presents the development and evaluation of the Cancer Ambulatory Patient Physical Function Longitudinal Evaluation Tool (CAPLET) as an adaptive response tool for routinely screening for physical dysfunction in oncology clinical practice.


In phase 1, 407 adult outpatients at Princess Margaret Cancer Centre completed the World Health Organization Disability Assessment Schedule (WHODAS) 2.0, Health Assessment Questionnaire Disability Index (HAQ-DI), EuroQuol-5D-3L ( EQ-5D-3L), and patient-reported outcome (PRO)-Eastern Cooperative Oncology Group (ECOG). CAPLET was developed based on a branching logic algorithm navigating patients to appropriate domains of HAQ-DI/WHOAS using their responses to the PRO-ECOG/EQ-5D-3L as screeners. Sensitivity/specificity of CAPLET screeners for HAQ-DI/WHODAS items were reported. In phase 2, CAPLET vs the WHODAS/HAQ-DI were alternatively administrated to 318 adult outpatients in a two-arm trial comparing time to completion and acceptability between the tools.


Using a patient’s ECOG status and the sum of the mobility, self-care, and usual activity dimensions of the EQ-5D-3L to dichotomize patients as with or without difficulty, CAPLET achieved a sensitivity > 90% against recommended WHODAS and HAQ-DI cutoffs for significant dysfunction. Sensitivity of screeners for capturing dysfunction in individual WHODAS/HAQ-DI items ranged from 85 to 100%. Compared to the HAQ-DI/WHODAS, CAPLET was associated with a 50% reduction in administration times and improved patient acceptability, while reducing question burden by 84% for half the sample population.


CAPLET improves the feasibility of capturing detailed assessments of patient-reported physical function in cancer outpatients.


Physical function Patient reported outcome Cancer Computer logic Sensitivity Specificity 


Funding information

This project was completed with support from Cancer Care Ontario, the Ontario Patient-Reported Outcomes for Symptoms and Toxicity Applied Clinical Research Unit (CCO ON-PROST ACRU), Lucy Wong Fund, Posluns Family Fund, and Alan B. Brown Chair in Molecular Genomics.

Compliance with ethical standards

All study protocols were approved by the research ethics board of the University Health Network in Toronto, Ontario, Canada.


A portion of the data included in this manuscript has been presented (1) at the American Society of Clinical Oncology Survivorship Symposium, January 29, 2017 and (2) at the American Society of Clinical Oncology Quality Care Symposium.

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

520_2018_4333_MOESM1_ESM.jpg (157 kb)
Supplementary Figure 1 (JPG 156 kb)
520_2018_4333_MOESM2_ESM.docx (18 kb)
Supplementary Table 1 (DOCX 18 kb)
520_2018_4333_MOESM3_ESM.docx (17 kb)
Supplementary Table 2 (DOCX 16 kb)
520_2018_4333_MOESM4_ESM.docx (14 kb)
Supplementary Table 3 (DOCX 14 kb)


  1. 1.
    McGrail K, Bryan S, Davis J (2011) Let’s all go to the PROM: the case for routine patient-reported outcome measurement in Canadian healthcare. Healthc Pap 11:8CrossRefGoogle Scholar
  2. 2.
    Dudgeon D, King S, Howell D, Green E, Gilbert J, Hughes E, Lalonde B, Angus H, Sawka C (2012) Cancer Care Ontario’s experience with implementation of routine physical and psychological symptom distress screening. Psychooncology 21:357–364CrossRefGoogle Scholar
  3. 3.
    Elliott D, Berney S, Harrold M, Skinner EH (2015) Key measurement and feasibility characteristics when selecting outcome measures. Current Physical Medicine and Rehabilitation Reports 3:255–267Google Scholar
  4. 4.
    Basch E, Torda P, Adams K (2013) Standards for patient-reported outcome-based performance measures. JAMA 310:139–140. CrossRefPubMedGoogle Scholar
  5. 5.
    Basch E, Snyder C, McNiff K, Brown R, Maddux S, Smith ML, Atkinson TM, Howell D, Chiang A, Wood W, Levitan N, Wu AW, Krzyzanowska M (2014) Patient-reported outcome performance measures in oncology. JOP 10:209–211.
  6. 6.
    Basch E, Reeve BB, Mitchell SA, Clauser SB, Minasian LM, Dueck AC, Mendoza TR, Hay J, Atkinson TM, Abernethy AP, Bruner DW, Cleeland CS, Sloan JA, Chilukuri R, Baumgartner P, Denicoff A, St. Germain D, O’Mara AM, Chen A, Kelaghan J, Bennett AV, Sit L, Rogak L, Barz A, Paul DB, Schrag D (2014) Development of the National Cancer Institute’s Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). JNCI 106(9):dju244Google Scholar
  7. 7.
    Repetto L, Fratino L, Audisio RA, Venturino A, Gianni W, Vercelli M, Parodi S, Dal Lago D, Gioia F, Monfardini S, Aapro MS, Serraino D, Zagonel V (2002) Comprehensive geriatric assessment adds information to Eastern Cooperative Oncology Group performance status in elderly cancer patients: an Italian Group for Geriatric Oncology Study. J Clin Oncol 20:494–502CrossRefGoogle Scholar
  8. 8.
    Bruce B, Fries JF (2003) The Stanford Health Assessment Questionnaire: dimensions and practical applications. Health Qual Life Outcomes 1(20):20CrossRefGoogle Scholar
  9. 9.
    Federici S, Bracalenti M, Meloni F, Luciano JV (2016) World Health Organization disability assessment schedule 2.0: an international systematic review. Disabil Rehab 39(23):2347–2380Google Scholar
  10. 10.
    Sutradhar R, Atzema C, Seow H, Earle C, Porter J, Howell D, Dudgeon D, Barbera L (2014) Is performance status associated with symptom scores? A population-based longitudinal study among cancer outpatients. J Palliat Care 30:99–107CrossRefGoogle Scholar
  11. 11.
    Aaronson NK, Ahmedzai S, Bergman B, Bullinger M, Cull A, Duez NJ, Filiberti A, Flechtner H, Fleishman SB, de Haes JC (1993) 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 85:365–376CrossRefGoogle Scholar
  12. 12.
    Howell D, Molloy S, Wilkinson K, Green E, Orchard K, Wang K, Liberty J (2015) Patient-reported outcomes in routine cancer clinical practice: a scoping review of use, impact on health outcomes, and implementation factors. Ann Oncol 26:1846–1858CrossRefGoogle Scholar
  13. 13.
    Gibbons C, Bower P, Lovell K, Valderas J, Skevington S (2016) Electronic quality of life assessment using computer-adaptive testing. J Med Internet Res 18:e240. CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Bass M, Morris S, Neapolitan R (2015) Utilizing multidimensional computer adaptive testing to mitigate burden with patient reported outcomes. AMIA Annu Symp Proc 2015:320–328Google Scholar
  15. 15.
    Petersen MA, Groenvold M, Aaronson NK, Chie W, Conroy T, Costantini A, Fayers P, Helbostad J, Holzner B, Kaasa S, Singer S, Velikova G, Young T (2010) Development of computerised adaptive testing (CAT) for the EORTC QLQ-C30 dimensions—general approach and initial results for physical functioning. Eur J Cancer 46:1352–1358. CrossRefPubMedGoogle Scholar
  16. 16.
    Helbostad JL, Holen JC, Jordhoy MS, Ringdal GI, Oldervoll L, Kaasa S, European Association for Palliative Care (EAPC) Research Network (2009) A first step in the development of an international self-report instrument for physical functioning in palliative cancer care: a systematic literature review and an expert opinion evaluation study. J Pain Symptom Manag 37:196–205CrossRefGoogle Scholar
  17. 17.
    Gilchrist LS, Galantino ML, Wampler M, Marchese VG, Morris GS, Ness KK (2009) A framework for assessment in oncology rehabilitation. Phys Ther 89:286–306CrossRefGoogle Scholar
  18. 18.
    Schubert CC, Gross C, Hurria A (2008) Functional assessment of the older patient with cancer. Oncology (Williston Park) 22:22 discussion 925, 928Google Scholar
  19. 19.
    Kluetz PG, Slagle A, Papadopoulos EJ, Johnson LL, Donoghue M, Kwitkowski VE, Chen WH, Sridhara R, Farrell AT, Keegan P, Kim G, Pazdur R (2016) Focusing on Core patient-reported outcomes in cancer clinical trials: symptomatic adverse events, physical function, and disease-related symptoms. Clin Cancer Res 22:1553–1558CrossRefGoogle Scholar
  20. 20.
    Brown JC, Harhay MO, Harhay MN (2016) Patient-reported versus objectively-measured physical function and mortality risk among cancer survivors. J Geriatr Oncol 7:108–115CrossRefGoogle Scholar
  21. 21.
    Montazeri A (2009) Quality of life data as prognostic indicators of survival in cancer patients: an overview of the literature from 1982 to 2008. Health Qual Life Outcomes 7:102CrossRefGoogle Scholar
  22. 22.
    Stucki G, Cieza A (2004) The international classification of functioning, disability and health (ICF) core sets for rheumatoid arthritis: a way to specify functioning. Ann Rheum Dis 63(Suppl 2):ii45Google Scholar
  23. 23.
    Mishra SI, Scherer RW, Geigle PM, Berlanstein DR, Topaloglu O, Gotay CC, Snyder C (2012) Exercise interventions on health-related quality of life for cancer survivors. Cochrane Database Syst Rev (8):CD007566. doi:CD007566Google Scholar
  24. 24.
    Pickard AS, Jiang R, Lin H, Rosenbloom S, Cella D (2016) Using patient-reported outcomes to compare relative burden of cancer: EQ-5D and functional assessment of cancer therapy-general in eleven types of cancer. Clin Ther 38:769–777CrossRefGoogle Scholar
  25. 25.
    Garin O, Ayuso-Mateos JL, Almansa J, Nieto M, Chatterji S, Vilagut G, Alonso J, Cieza A, Svetskova O, Burger H, Racca V, Francescutti C, Vieta E, Kostanjsek N, Raggi A, Leonardi M, Ferrer M, MHADIE consortium (2010) Validation of the “World Health Organization Disability Assessment Schedule, WHODAS-2” in patients with chronic diseases. Health Qual Life Outcomes 8:51CrossRefGoogle Scholar
  26. 26.
    Rabin R, Gudex C, Selai C, Herdman M (2014) From translation to version management: a history and review of methods for the cultural adaptation of the EuroQol Five-Dimensional Questionnaire. Value Health 17:70–76. CrossRefPubMedGoogle Scholar
  27. 27.
    Andrews G, Kemp A, Sunderland M, Von Korff M, Ustun TB (2009) Normative data for the 12 item WHO disability assessment schedule 2.0. PLoS One 4:e8343. CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Krishnan E, Sokka T, Häkkinen A, Hubert H, Hannonen P (2004) Normative values for the Health Assessment Questionnaire Disability Index: benchmarking disability in the general population. Arthritis Rheum 50:953–960CrossRefGoogle Scholar
  29. 29.
    Naughton MJ, Weaver KE (2014) Physical and mental health among cancer survivors: considerations for long-term care and quality of life. N C Med J 75:283–286PubMedPubMedCentralGoogle Scholar
  30. 30.
    Morris S, Bass M, Lee M, Neapolitan RE (2017) Advancing the efficiency and efficacy of patient reported outcomes with multivariate computer adaptive testing. J Am Med Inform Assoc 24:897–902. CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Naik H, Qiu X, Brown MC, Mahler M, Hon H, Tiessen K, Thai H, Ho V, Gonos C, Charow R, Pat V, Irwin M, Herzog L, Ho A, Xu W, Howell D, Seung SJ, Liu G, Mittmann N (2016) Cancer patients? Willingness to routinely complete the EQ-5D instrument at clinic visits. J Popul Ther Clin Pharmacol 23:e204Google Scholar
  32. 32.
    Janssen MF, Pickard AS, Golicki D, Gudex C, Niewada M, Scalone L, Swinburn P, Busschbach J (2013) Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: a multi-country study 22:1717–1727. doi:
  33. 33.
    Patel S, Park H, Bonato P, Chan L, Rodgers M (2012) A review of wearable sensors and systems with application in rehabilitation. J Neuroeng Rehabil 20(9):21Google Scholar
  34. 34.
    De Buyser SL, Petrovic M, Taes YE, Vetrano DL, Onder G (2014) A multicomponent approach to identify predictors of hospital outcomes in older in-patients: a multicentre, observational study. PLoS One 9:e115413CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Elizabeth Hall
    • 1
  • Emily Tam
    • 1
  • Mindy Liang
    • 1
  • Quihuang Zhang
    • 2
  • Lin Liu
    • 2
  • Lauren Wong
    • 1
  • Samantha Sarabia
    • 1
  • Sabrina Yeung
    • 1
  • Gursharan Gill
    • 1
  • Lawson Eng
    • 1
  • Andrea Perez-Cosio
    • 1
  • M. Catherine Brown
    • 1
  • Wei Xu
    • 2
  • Madeline Li
    • 3
  • Nicole Mittmann
    • 4
  • Jennifer Jones
    • 5
  • Doris Howell
    • 3
    • 6
    Email author
  • Geoffrey Liu
    • 1
    • 7
    Email author
  1. 1.Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre and Departments of Medicine and Epidemiology, Dalla Lana School of Public HealthUniversity of TorontoTorontoCanada
  2. 2.Department of Biostatistics, Princess Margaret Cancer Centre, Dalla Lana School of Public HealthUniversity of TorontoTorontoCanada
  3. 3.Psychosocial OncologyPrincess Margaret Cancer CentreTorontoCanada
  4. 4.Sunnybrook Health Sciences CentreTorontoCanada
  5. 5.Survivorship ProgramPrincess Margaret Cancer CentreTorontoCanada
  6. 6.Lawrence Bloomberg School of NursingUniversity of TorontoTorontoCanada
  7. 7.Department of Epidemiology, Dalla Lana School of Public Health, Departments of Medicine and BiophysicsUniversity of TorontoTorontoCanada

Personalised recommendations