Using the EORTC-QLQ-C30 in clinical practice for patient management

Identifying scores requiring a clinician's attention

Claire Snyder, Amanda L. Blackford, Toru Okuyama, Tatsuo Akechi, Hiroko Yamashita, Tatsuya Toyama, Michael A Carducci, Albert W Wu

Research output: Contribution to journalArticle

Abstract

Purpose Patient-reported outcomes (PROs) are used increasingly for individual patient management. Identifying which PRO scores require a clinician's attention is an ongoing challenge. Previous research used a needs assessment to identify EORTC-QLQ-C30 cutoff scores representing unmet needs. This analysis attempted to replicate the previous findings in a new and larger sample. Methods This analysis used data from 408 Japanese ambulatory breast cancer patients who completed the QLQ-C30 and Supportive Care Needs Survey-Short Form-34 (SCNS-SF34). Applying the methods used previously, SCNS-SF34 item/domain scores were dichotomized as no versus some unmet need. We calculated area under the receiver operating characteristic curve (AUC) to evaluate QLQ-C30 scores' ability to discriminate between patients with no versus some unmet need based on SCNS-SF34 items/domains. For QLQ-C30 domains with AUC C 0.70, we calculated the sensitivity, specificity, and predictive value of various cutoffs for identifying unmet needs. We hypothesized that compared to our original analysis, (1) the same six QLQ-C30 domains would have AUC C 0.70, (2) the same SCNS-SF34 items would be best discriminated by QLQ-C30 scores, and (3) the sensitivity and specificity of our original cutoff scores would be supported. Results The findings from our original analysis were supported. The same six domains with AUC C 0.70 in the original analysis had AUC C 0.70 in this new sample, and the same SCNS-SF34 item was best discriminated by QLQ-C30 scores. Cutoff scores were identified with sensitivity C0.84 and specificity C0.54. Conclusion Given these findings' concordance with our previous analysis, these QLQ-C30 cutoffs could be implemented in clinical practice and their usefulness evaluated.

Original languageEnglish (US)
Pages (from-to)2685-2691
Number of pages7
JournalQuality of Life Research
Volume22
Issue number10
DOIs
StatePublished - Dec 2013

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Practice Management
Area Under Curve
Sensitivity and Specificity
Needs Assessment
ROC Curve
Surveys and Questionnaires
Breast Neoplasms
Research
Patient Reported Outcome Measures

Keywords

  • Cancer
  • Clinical practice
  • EORTC-QLQ-C30
  • Patient-reported outcomes

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Medicine(all)

Cite this

Using the EORTC-QLQ-C30 in clinical practice for patient management : Identifying scores requiring a clinician's attention. / Snyder, Claire; Blackford, Amanda L.; Okuyama, Toru; Akechi, Tatsuo; Yamashita, Hiroko; Toyama, Tatsuya; Carducci, Michael A; Wu, Albert W.

In: Quality of Life Research, Vol. 22, No. 10, 12.2013, p. 2685-2691.

Research output: Contribution to journalArticle

Snyder, Claire ; Blackford, Amanda L. ; Okuyama, Toru ; Akechi, Tatsuo ; Yamashita, Hiroko ; Toyama, Tatsuya ; Carducci, Michael A ; Wu, Albert W. / Using the EORTC-QLQ-C30 in clinical practice for patient management : Identifying scores requiring a clinician's attention. In: Quality of Life Research. 2013 ; Vol. 22, No. 10. pp. 2685-2691.
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abstract = "Purpose Patient-reported outcomes (PROs) are used increasingly for individual patient management. Identifying which PRO scores require a clinician's attention is an ongoing challenge. Previous research used a needs assessment to identify EORTC-QLQ-C30 cutoff scores representing unmet needs. This analysis attempted to replicate the previous findings in a new and larger sample. Methods This analysis used data from 408 Japanese ambulatory breast cancer patients who completed the QLQ-C30 and Supportive Care Needs Survey-Short Form-34 (SCNS-SF34). Applying the methods used previously, SCNS-SF34 item/domain scores were dichotomized as no versus some unmet need. We calculated area under the receiver operating characteristic curve (AUC) to evaluate QLQ-C30 scores' ability to discriminate between patients with no versus some unmet need based on SCNS-SF34 items/domains. For QLQ-C30 domains with AUC C 0.70, we calculated the sensitivity, specificity, and predictive value of various cutoffs for identifying unmet needs. We hypothesized that compared to our original analysis, (1) the same six QLQ-C30 domains would have AUC C 0.70, (2) the same SCNS-SF34 items would be best discriminated by QLQ-C30 scores, and (3) the sensitivity and specificity of our original cutoff scores would be supported. Results The findings from our original analysis were supported. The same six domains with AUC C 0.70 in the original analysis had AUC C 0.70 in this new sample, and the same SCNS-SF34 item was best discriminated by QLQ-C30 scores. Cutoff scores were identified with sensitivity C0.84 and specificity C0.54. Conclusion Given these findings' concordance with our previous analysis, these QLQ-C30 cutoffs could be implemented in clinical practice and their usefulness evaluated.",
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T1 - Using the EORTC-QLQ-C30 in clinical practice for patient management

T2 - Identifying scores requiring a clinician's attention

AU - Snyder, Claire

AU - Blackford, Amanda L.

AU - Okuyama, Toru

AU - Akechi, Tatsuo

AU - Yamashita, Hiroko

AU - Toyama, Tatsuya

AU - Carducci, Michael A

AU - Wu, Albert W

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N2 - Purpose Patient-reported outcomes (PROs) are used increasingly for individual patient management. Identifying which PRO scores require a clinician's attention is an ongoing challenge. Previous research used a needs assessment to identify EORTC-QLQ-C30 cutoff scores representing unmet needs. This analysis attempted to replicate the previous findings in a new and larger sample. Methods This analysis used data from 408 Japanese ambulatory breast cancer patients who completed the QLQ-C30 and Supportive Care Needs Survey-Short Form-34 (SCNS-SF34). Applying the methods used previously, SCNS-SF34 item/domain scores were dichotomized as no versus some unmet need. We calculated area under the receiver operating characteristic curve (AUC) to evaluate QLQ-C30 scores' ability to discriminate between patients with no versus some unmet need based on SCNS-SF34 items/domains. For QLQ-C30 domains with AUC C 0.70, we calculated the sensitivity, specificity, and predictive value of various cutoffs for identifying unmet needs. We hypothesized that compared to our original analysis, (1) the same six QLQ-C30 domains would have AUC C 0.70, (2) the same SCNS-SF34 items would be best discriminated by QLQ-C30 scores, and (3) the sensitivity and specificity of our original cutoff scores would be supported. Results The findings from our original analysis were supported. The same six domains with AUC C 0.70 in the original analysis had AUC C 0.70 in this new sample, and the same SCNS-SF34 item was best discriminated by QLQ-C30 scores. Cutoff scores were identified with sensitivity C0.84 and specificity C0.54. Conclusion Given these findings' concordance with our previous analysis, these QLQ-C30 cutoffs could be implemented in clinical practice and their usefulness evaluated.

AB - Purpose Patient-reported outcomes (PROs) are used increasingly for individual patient management. Identifying which PRO scores require a clinician's attention is an ongoing challenge. Previous research used a needs assessment to identify EORTC-QLQ-C30 cutoff scores representing unmet needs. This analysis attempted to replicate the previous findings in a new and larger sample. Methods This analysis used data from 408 Japanese ambulatory breast cancer patients who completed the QLQ-C30 and Supportive Care Needs Survey-Short Form-34 (SCNS-SF34). Applying the methods used previously, SCNS-SF34 item/domain scores were dichotomized as no versus some unmet need. We calculated area under the receiver operating characteristic curve (AUC) to evaluate QLQ-C30 scores' ability to discriminate between patients with no versus some unmet need based on SCNS-SF34 items/domains. For QLQ-C30 domains with AUC C 0.70, we calculated the sensitivity, specificity, and predictive value of various cutoffs for identifying unmet needs. We hypothesized that compared to our original analysis, (1) the same six QLQ-C30 domains would have AUC C 0.70, (2) the same SCNS-SF34 items would be best discriminated by QLQ-C30 scores, and (3) the sensitivity and specificity of our original cutoff scores would be supported. Results The findings from our original analysis were supported. The same six domains with AUC C 0.70 in the original analysis had AUC C 0.70 in this new sample, and the same SCNS-SF34 item was best discriminated by QLQ-C30 scores. Cutoff scores were identified with sensitivity C0.84 and specificity C0.54. Conclusion Given these findings' concordance with our previous analysis, these QLQ-C30 cutoffs could be implemented in clinical practice and their usefulness evaluated.

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KW - Clinical practice

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