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Anthea Cree



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    MA19 - Looking at PROs in Greater Detail - What Patients Actually Want and Expect (ID 147)

    • Event: WCLC 2019
    • Type: Mini Oral Session
    • Track: Treatment in the Real World - Support, Survivorship, Systems Research
    • Presentations: 1
    • Now Available
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      MA19.09 - Assessing Clinical Frailty in Advanced Lung Cancer Patients - An Opportunity to Improve Patient Outcomes? (Now Available) (ID 2363)

      11:30 - 13:00  |  Author(s): Anthea Cree

      • Abstract
      • Presentation
      • Slides

      Background

      The median age of non-small cell lung cancer (NSCLC) diagnosis in England is 73 years. At that age, 40% of the general population has some degree of clinical frailty which may impact survival, quality of life, anti-cancer treatment tolerability and access to clinical trials. However, clinical frailty is often not addressed or managed at the time of anti-cancer treatments. This project was designed to integrate frailty assessments and build frailty pathways within an advanced cancer care setting in order to better support patients and improve outcomes.

      Method

      This quality improvement project that used Plan-Do-Study-Act (PDSA) methodology. Phase one of the project focused on establishing a multidisciplinary team to integrate a frailty screening tool, the Rockwood Clinical Frailty Scale (CFS), into standard clinical practice. The primary aim was to implement and screen ≥80% of all new lung cancer patients at a high-volume tertiary cancer centre. The secondary aim was to explore the correlation of CFS with age, performance status (PS), treatment selection and systemic anti-cancer treatment (SACT) tolerability. Specialised training was provided to the clinical team and the CFS was integrated from 26/11/2018 on an electronic form routinely completed by clinicians. A digital dashboard was set-up to monitor real-time data and the frail group was defined as CFS score >3. Data cut-off for this analysis was 29-03-2019.

      Result

      335 lung cancer patients were screened using CSF by a team of 20 clinicians with a compliance rate of 89%. There was a strong correlation between PS and CFS (r= 0.77, p<0.01). The distribution of both CFS and PS correlated with ageing (r= 0.2 and r= 0.17, respectively; p<0.01). Patients ≥70 years were more likely to be frail (56% vs 40%; OR 1.4, 95%CI 1.2-1.7; p<0.01). Frailty reduced the likelihood of receiving any anti-cancer treatment by 20%. Amongst those who started SACT, patients classed as frail were less likely to go beyond the first cycle of treatment (64% vs 91%; OR 0.7, 95%CI 0.5-0.9; p<0.01).

      Conclusion

      CFS screening is feasible within a busy clinical practice when incorporated as a digital tool. CFS helps to identify patients who may potentially benefit from specialised frailty assessment and management. This could ultimately be used to better inform on treatment selection, and support requirements during treatment, to improve outcomes for patients in the future.

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