Pooling of cross-cultural PRO data in multinational clinical trials: How much can poor measurement affect statistical power?

Abstract

Aims

Cultural differences and/or poor linguistic validation of patient-reported outcome (PRO) instruments may result in differences in the assessment of the targeted concept across languages. In the context of multinational clinical trials, these measurement differences may add noise and potentially measurement bias to treatment effect estimation. Our objective was to explore the potential effect on treatment effect estimation of the “contamination” of a cultural subgroup by a flawed PRO measurement.

Methods

We ran a simulation exercise in which the distribution of the score in the overall sample was considered a mixture of two normal distributions: a standard normal distribution was assumed in a “main” subgroup and a normal distribution which differed either in mean (bias) or in variance (noise) in a “contaminated” subgroup (the subgroup with potential flaws in the PRO measurement). The observed power was compared to the expected power (i.e., the power that would have been observed if the subgroup had not been contaminated).

Results

Even if differences between the expected and observed power were small, some substantial differences were obtained (up to a 0.375 point drop in power). No situation was systematically protected against loss of power.

Conclusion

The impact of poor PRO measurement in a cultural subgroup may induce a notable drop in the study power and consequently reduce the chance of showing an actual treatment effect. These results illustrate the importance of the efforts to optimize conceptual and linguistic equivalence of PRO measures when pooling data in international clinical trials.

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References

  1. 1.

    Bullinger, M., Anderson, R., Cella, D., & Aaronson, N. (1993). Developing and evaluating cross-cultural instruments from minimum requirements to optimal models. Quality of Life Research, 2(6), 451–459.

    CAS  PubMed  Article  Google Scholar 

  2. 2.

    Herdman, M., Fox-Rushby, J., & Badia, X. (1997). ‘equivalence’ and the translation and adaptation of health-related quality of life questionnaires. Quality of Life Research, 6(3), 237–247.

    CAS  PubMed  Article  Google Scholar 

  3. 3.

    Herdman, M., Fox-Rushby, J., & Badia, X. (1998). A model of equivalence in the cultural adaptation of HRQoL instruments: The universalist approach. Quality of Life Research, 7, 323–335.

    CAS  PubMed  Article  Google Scholar 

  4. 4.

    Schmidt, S., & Bullinger, M. (2003). Current issues in cross-cultural quality of life instrument development. Archives of Physical Medication Rehabilitation, 84(4 Suppl 2), S29–S34.

    Article  Google Scholar 

  5. 5.

    Teresi, J. A. (2006). Overview of quantitative measurement methods: Equivalence, invariance, and differential item functioning in health applications. Medical Care, 44(11 Suppl 3), 39–45.

    Article  Google Scholar 

  6. 6.

    Regnault, A., Herdman, M. (2014). Using quantitative methods within the Universalist model framework to explore the cross-cultural equivalence of patient-reported outcome instruments. Quality of Life Research. doi:10.1007/s11136-014-0722-8

  7. 7.

    Bjorner, J. B., Kreiner, S., Ware, J. E., Damsgaard, M. T., & Bech, P. (1998). Differential item functioning in the Danish translation of the SF-36. Journal of Clinical Epidemiology, 51(11), 1189–1202.

    CAS  PubMed  Article  Google Scholar 

  8. 8.

    Scott, N. W., Fayers, P., Bottomley, A., Aaronson, N. K., de Graef, A., Groenvold, M., et al. (2006). Comparing translations of the EORTC QLQ-C30 using differential item functioning analyses. Quality of Life Research, 15(6), 1103–1115.

    CAS  PubMed  Article  Google Scholar 

  9. 9.

    Robitail, S., Ravens-Sieberer, U., Simeoni, M. C., Rajmil, L., Bruil, J., Power, M., et al. (2007). Testing the structural and cross-cultural validity of the KIDSCREEN-27 quality of life questionnaire. Quality of Life Research, 16(8), 1335–1345.

    PubMed  Article  Google Scholar 

  10. 10.

    Scott, N. W., Fayers, P., Bottomley, A., Aaronson, N. K., de Graef, A., Groenvold, M., et al. (2007). The use of differential item functioning analyses to identify cultural differences in responses to the EORTC QLQ-C30. Quality of Life Research, 16(1), 115–129.

    CAS  PubMed  Article  Google Scholar 

  11. 11.

    Regnault, A., Marfatia, S., Louie, M., Mear, I., Meunier, J., & Viala-Danten, M. (2009). Satisfactory cross-cultural validity of the ACTG symptom distress module in HIV-1-infected antiretroviral-naive patients. Clinical Trials, 6(6), 574–584.

    PubMed  Article  Google Scholar 

  12. 12.

    Scott, N. W., Fayers, P., Bottomley, A., Aaronson, N. K., de Graef, A., Groenvold, M., et al. (2009). The practical impact of differential item functioning analyses in a health-related quality of life instrument. Quality of Life Research, 18(8), 1125–1130.

    PubMed  Article  Google Scholar 

  13. 13.

    Wild, D., Eremenco, S., Mear, I., Martin, M., Houchin, C., Gawlicki, M., et al. (2009). Multinational trials—Recommendations on the translations required, approaches to using the same language in different countries, and the approaches to support pooling the data: the ISPOR Patient-Reported Outcomes Translation and Linguistic Validation Good Research Practices Task Force report. Value in Health, 12(4), 430–440.

    PubMed  Article  Google Scholar 

  14. 14.

    Acquadro, C., Conway, K., Giroudet, C., & Mear, I. (2012). Linguistic validation manual for health outcome assessments. Lyon: MAPI Institute.

    Google Scholar 

Download references

Acknowledgments

This paper was reviewed by membership of the International Society for Quality of Life Research (ISOQOL) Translation and Cultural Adaptation Special Interest Group.

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Correspondence to Antoine Regnault.

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On behalf of the ISOQOL Translation and Cultural Adaptation Special Interest Group.

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Regnault, A., Hamel, J. & Patrick, D.L. Pooling of cross-cultural PRO data in multinational clinical trials: How much can poor measurement affect statistical power?. Qual Life Res 24, 273–277 (2015). https://doi.org/10.1007/s11136-014-0765-x

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Keywords

  • Pooling of data
  • Cross-cultural research
  • Simulations
  • Questionnaires