TY - JOUR
T1 - Using the EORTC-QLQ-C30 in clinical practice for patient management
T2 - Identifying scores requiring a clinician's attention
AU - Snyder, Claire F.
AU - Blackford, Amanda L.
AU - Okuyama, Toru
AU - Akechi, Tatsuo
AU - Yamashita, Hiroko
AU - Toyama, Tatsuya
AU - Carducci, Michael A.
AU - Wu, Albert W.
N1 - Funding Information:
Acknowledgments This analysis was supported by the American Cancer Society (MRSG-08-011-01-CPPB). The original data collection was supported in part by Grants-in-Aid for Cancer Research and the Third Term Comprehensive 10-Year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare, Japan. Drs. Snyder and Carducci are members of the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins (P30CA006973). The funding sources had no role in study design, data collection, analysis, interpretation, writing, or decision to submit the manuscript for publication.
PY - 2013/12
Y1 - 2013/12
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.
KW - Cancer
KW - Clinical practice
KW - EORTC-QLQ-C30
KW - Patient-reported outcomes
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U2 - 10.1007/s11136-013-0387-8
DO - 10.1007/s11136-013-0387-8
M3 - Article
C2 - 23532341
AN - SCOPUS:84892819093
SN - 0962-9343
VL - 22
SP - 2685
EP - 2691
JO - Quality of Life Research
JF - Quality of Life Research
IS - 10
ER -