Advertisement

Quality of Life Research

, Volume 27, Issue 5, pp 1357–1367 | Cite as

PROMIS depression measures perform similarly to legacy measures relative to a structured diagnostic interview for depression in cancer patients

  • Kerrie Clover
  • Sylvie D. Lambert
  • Christopher Oldmeadow
  • Benjamin Britton
  • Madeleine T. King
  • Alex J. Mitchell
  • Gregory Carter
Article

Abstract

Purpose

To assess the convergent validity of the Patient-Reported Outcomes Measurement Information System (PROMIS) depression measures relative to legacy measures and criterion validity against a structured diagnostic interview for depression in an oncology sample.

Methods

132 oncology/haematology outpatients completed the PROMIS Depression Computer Adaptive Test (PROMIS-D-CAT) and PROMIS Depression Short Form (PROMIS-D-SF) along with seven legacy measures: Beck Depression Inventory (BDI); Centre for Epidemiological Studies Depression (CES-D); Depression, Anxiety and Stress Scale; Hospital Anxiety and Depression Scale; Patient Health Questionnaire; Distress Thermometer and PSYCH-6. Correlations, area under the curve (AUC) and diagnostic accuracy statistics were calculated with Structured Clinical Interview as the gold standard.

Results

Both PROMIS measures correlated with all legacy measures at p < .001 (ρ = 0.589–0.810) and all AUCs (> 0.800) were comparable. At the cut-off points for mild depression of 53, the PROMIS measures had sensitivity (0.83 for PROMIS-D-CAT and 0.80 for PROMIS-D-SF) similar to or better than 6/7 legacy measures with high negative predictive value (> 90%). At cut-off points of 60 for moderate depression, PROMIS measures had specificity > 90%, similar to or better than all legacy measures and positive predictive value ≥ 0.50 (similar to 5/7 legacy measures).

Conclusions

The convergent and criterion validity of the PROMIS depression measures in cancer populations was confirmed, although the optimal cut-off points are not established. PROMIS measures were briefer than BDI-II and CES-D but do not offer any advance in terms of diagnostic accuracy, reduced response burden or cost over other legacy measures of depression in oncology patients.

Keywords

Psycho-oncology Depression Questionnaire development Cancer 

Notes

Acknowledgements

We would like to thank our Psychologist interviewers and all of the participants who gave so generously of their time. Thanks also to Jessica Searston for assistance with manuscript preparation.

Funding

This study was funded by Calvary Mater Newcastle (Grant Number 11-09) and the Centre for Translational Neuroscience and Mental Health of the University of Newcastle (Australia) provided funding for statistical analysis. Professor King is supported by the Australian Government through Cancer Australia. Dr Lambert was initially supported by a National Health and Medical Research Council Research Fellowship (APP1012869) during data collection and by an FRQS Junior 1 Research Scholar Award subsequently.

Compliance with ethical standards

Conflict of interest

Kerrie Clover declares that she has no conflict of interest. Sylvie D. Lambert declares that she has no conflict of interest. Christopher Oldmeadow declares that he has no conflict of interest. Madeleine T. King declares that she has no conflict of interest Benjamin Britton declares that he has no conflict of interest. Alex J Mitchell declares that he has no conflict of interest. Gregory L. Carter declares that he has no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or National Research Committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

References

  1. 1.
    Institute of Medicine Report 2008, (IOM) (2008). Cancer care for the whole patient: Meeting psychosocial health needs. The National Academies Press: Washington, DC.Google Scholar
  2. 2.
    Alex, J., Mitchell, N., Hussain, L., & Grainger, P. S. (2011). Identification of patient-reported distress by clinical nurse specialists in routine oncology practice: a multicentre UK study. Psychooncology, 20(10) 1076–1083.CrossRefGoogle Scholar
  3. 3.
    Holland, J. C., & Bultz, B. D. (2007). The NCCN guideline for distress management: A case for making distress the sixth vital sign. Journal of the National Comprehensive Cancer Network, 5(1), 3–7.CrossRefPubMedGoogle Scholar
  4. 4.
    American College of Surgeons Commission on Cancer. Cancer Program Standards 2012 Version 1.1: Ensuring patient-centered care. Available at: http://www.facs.org/cancer/coc/programstandards2012.html. Accessed March 2017.
  5. 5.
    Carlson, L. E., Waller, A., & Mitchell, A. J. (2012). Screening for distress and unmet needs in patients with cancer: Review and recommendations. Journal of Clinical Oncology, 30(11), 1160–1177.CrossRefPubMedGoogle Scholar
  6. 6.
    Lambert, S. D., Clover, K., Pallant, J. F., Britton, B., King, M. T., Mitchell, A. J., & Carter, G. (2015). Making sense of variations in prevalence estimates of depression in cancer: A co-calibration of commonly used depression scales using Rasch Analysis. Journal of the National Comprehensive Cancer Network, 13(10), 1203–1211.CrossRefPubMedGoogle Scholar
  7. 7.
    Mitchell, A. J., Meader, N., Davies, E., Clover, K., Carter, G. L., Loscalzo, M. J., et al. (2012). Meta-analysis of screening and case finding tools for depression in cancer: evidence based recommendations for clinical practice on behalf of the Depression in Cancer Care consensus group. Journal of Affective Disorders, 140(2), 149–160.CrossRefPubMedGoogle Scholar
  8. 8.
    Cella, D., Riley, W., Stone, A., Rothrock, N., Reeve, B., Yount, S., et al. (2010). Initial adult health item banks and first wave testing of the patient-reported outcomes measurement information system (PROMIS™) network: 2005–2008. Journal of Clinical Epidemiology, 63(11), 1179.CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Choi, S. W., Reise, S. P., Pilkonis, P. A., Hays, R. D., & Cella, D. (2010). Efficiency of static and computer adaptive short forms compared to full-length measures of depressive symptoms. Quality of Life Research, 19(1), 125–136.CrossRefPubMedGoogle Scholar
  10. 10.
    Baum, G., Basen-Engquist, K., Swartz, M. C., Parker, P. A., & Carmack, C. L. (2014). Comparing PROMIS computer-adaptive tests to the Brief Symptom Inventory in patients with prostate cancer. Quality of Life Research, 23(7), 2031–2035.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Cella, D., Choi, S., Garcia, S., Cook, K. F., Rosenbloom, S., Lai, J. S., Tatum, D. S., & Gershon, R. (2014). Setting standards for severity of common symptoms in oncology using the PROMIS item banks and expert judgment. Quality of Life Research, 23(10), 2651–2661.CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Lazenby, M., Ercolano, E., Grant, M., Holland, J. C., Jacobsen, P. B., & McCorkle, R. (2015). Supporting commission on cancer–mandated psychosocial distress screening with implementation strategies. Journal of Oncology Practice, 11(3), e413–e420.  https://doi.org/10.1200/JOP.2014.002816.CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Maxim, L. D., Niebo, R., & Utell, M. J. (2014). Screening tests: A review with examples. Inhalation Toxicology, 26(13), 811–828.  https://doi.org/10.3109/08958378.2014.955932.CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Mitchell, A. J. (2007). Pooled results from 38 analyses of the accuracy of distress thermometer and other ultra-short methods of detecting cancer-related mood disorders. Journal of Clinical Oncology, 25(29), 4670–4681.CrossRefPubMedGoogle Scholar
  15. 15.
    Clover, K., Carter, G., Adams, C., Hickie, I., & Davenport, T. (2009). Concurrent validity of the PSYCH-6, a very short scale for detecting anxiety and depression, among oncology outpatients. Australian New Zealand Journal of Psychiatry, 43(7), 682–688.CrossRefPubMedGoogle Scholar
  16. 16.
    Wagner, L. I., Schink, J., Bass, M., Patel, S., Diaz, M. V., Rothrock, N., et al. (2015). Bringing PROMIS to practice: Brief and precise symptom screening in ambulatory cancer care. Cancer, 121(6), 927–934.CrossRefPubMedGoogle Scholar
  17. 17.
    Stone, A. A., Broderick, J. E., Junghaenel, D. U., Schneider, S., & Schwartz, J. E. (2016). PROMIS fatigue, pain intensity, pain interference, pain behavior, physical function, depression, anxiety, and anger scales demonstrate ecological validity. Journal of Clinical Epidemiology, 74, 194–206.CrossRefPubMedGoogle Scholar
  18. 18.
    Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Manual for The Beck Depression Inventory Second Edition (BDI-II). San Antonio: Psychological Corporation.Google Scholar
  19. 19.
    Mitchell, A. J., Meader, N., & Symonds, P. (2010) Diagnostic validity of the Hospital Anxiety and Depression Scale (HADS) in cancer and palliative settings: A meta-analysis. Journal of Affective Disorders 126(3), 335–348.CrossRefPubMedGoogle Scholar
  20. 20.
    Vodermaier, A., & Millman, R. D. (2011). Accuracy of the hospital anxiety and depression scale as a screening tool in cancer patients: A systematic review and meta-analysis. Supportive Care in Cancer 19(12), 1899–1908.CrossRefPubMedGoogle Scholar
  21. 21.
    Zigmond, A. S., & Snaith, R. P. (1983). The hospital anxiety and depression scale. Acta Psychiatrica Scandinavica, 67(6), 361–370.  https://doi.org/10.1111/j.1600-0447.1983.tb09716.x.CrossRefPubMedGoogle Scholar
  22. 22.
    National Comprehensive Cancer Network (2003) Distress management. Clinical practice guidelines. Journal of the National Comprehensive Cancer Network. 1(3), 344–374.CrossRefGoogle Scholar
  23. 23.
    Hickie, I. B., Koschera, A., Davenport, T. A., Naismith, S. L., & Scott, E. M. (2001). Comorbidity of common mental disorders and alcohol or other substance misuse in Australian general practice. The Medical Journal of Australia, 175, S31–S36.PubMedGoogle Scholar
  24. 24.
    First, M. B., Gibbon, M., Spitzer, R. L., & Williams, J. B. (2002). Structured Clinical Interview for DSM-IV-TR Axis I Disorders: Research Version. Biometrics Research Department, New York State Psychiatric Institute.Google Scholar
  25. 25.
    Clover, K. A., Rogers, K., Britton, B., Oldmeadow, C., Attia, J., & Carter, G. L. (2017) Reduced prevalence of pain and distress during four years of screening with QUICATOUCH in Australian oncology patients. European Journal of Cancer Care.Google Scholar
  26. 26.
    Dancy, C. P., & Reidy, J. (2004). Statistics without maths for psychology. Harlow: Pearson Education Limited.Google Scholar
  27. 27.
    Swets, J. A. (1988). Measuring the accuracy of diagnostic systems. Science, 240(4857), 1285.CrossRefPubMedGoogle Scholar
  28. 28.
    Pilkonis, P. A., Choi, S. W., Reise, S. P., Stover, A. M., Riley, W. T., & Cella, D. (2011). Item banks for measuring emotional distress from the Patient-Reported Outcomes Measurement Information System (PROMIS®): Depression, anxiety, and anger. Assessment, 18(3), 263–283.CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Centre for Epidemiologic Studies. (1970) Centre for Epidemiologic Studies Depression Scale (CES-D). Rockville: National Institute of Mental Health.Google Scholar
  30. 30.
    Fischer, H. F., Klug, C., Roeper, K., Blozik, E., Edelmann, F., Eisele, M., et al. (2014). Screening for mental disorders in heart failure patients using computer-adaptive tests. Quality of Life Research, 23(5), 1609–1618.CrossRefPubMedGoogle Scholar
  31. 31.
    Clover, K., Carter, G., Mackinnon, A., & Adams, C. (2009). Is my patient suffering clinically significant emotional distress? Demonstration of a probabilities approach to evaluating algorithms for screening for distress. Supportive Care in Cancer, 17, 1455–1462.CrossRefPubMedGoogle Scholar
  32. 32.
    Health Measures (2016). Assessment Centre Pricing Information. http://www.healthmeasures.net/images/LearnMore/Assessment_Center_Pricing_Information_07252016.pdf. Accessed 29 May 2017.
  33. 33.
    Krebber, A. M., Buffart, L. M., Kleijn, G., Riepma, I. C., Bree, R., Leemans, C. R., et al. (2014) Prevalence of depression in cancer patients: a meta-analysis of diagnostic interviews and self-report instruments. Psycho-Oncology, 23(2), 121–130.CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Psycho-Oncology Service, Calvary Mater NewcastleNewcastleAustralia
  2. 2.Centre for Translational Neuroscience and Mental Health, Faculty of Health and MedicineUniversity of NewcastleNewcastleAustralia
  3. 3.Ingram School of NursingMcGill University & St. Marys’ Research CentreMontrealCanada
  4. 4.Clinical Research Design, Information Technology and Statistical Support (CReDITSS) Hunter Medical Research InstituteNew LambtonAustralia
  5. 5.School of Psychology and Sydney Medical SchoolUniversity of SydneySydneyAustralia
  6. 6.University of Leicester, Cancer & Molecular MedicineLeicesterUK

Personalised recommendations