Frailty and Bone Disease
Cross-source consensus on Frailty and Bone Disease from 1 sources and 5 claims.
1 sources · 5 claims
Uses
How it works
Evidence quality
Highlighted claims
- Hospital admission and comorbidity data will be used to derive and externally validate several frailty tools. — Blood Cancer Clinical Trials Long-term Follow-up Using Integrated Healthcare Systems Data (BLISS): protocol for a data-linkage study integrating randomised clinical trials with national healthcare systems data
- The simplified International Myeloma Working Group frailty scale will use age, Charlson Comorbidity Index, and ECOG performance status to classify patients as frail or non-frail. — Blood Cancer Clinical Trials Long-term Follow-up Using Integrated Healthcare Systems Data (BLISS): protocol for a data-linkage study integrating randomised clinical trials with national healthcare systems data
- Skeletal-related events will be derived from healthcare systems data using ICD-10 and OPCS-4 codes in HES and radiotherapy data. — Blood Cancer Clinical Trials Long-term Follow-up Using Integrated Healthcare Systems Data (BLISS): protocol for a data-linkage study integrating randomised clinical trials with national healthcare systems data
- Frailty classifications will be externally validated against outcomes including overall survival, progression-free survival, and early mortality. — Blood Cancer Clinical Trials Long-term Follow-up Using Integrated Healthcare Systems Data (BLISS): protocol for a data-linkage study integrating randomised clinical trials with national healthcare systems data
- BLISS will examine myeloma bone disease as an important endpoint that has been difficult to assess in randomised controlled trials. — Blood Cancer Clinical Trials Long-term Follow-up Using Integrated Healthcare Systems Data (BLISS): protocol for a data-linkage study integrating randomised clinical trials with national healthcare systems data