Potentially inappropriate prescribing in older adults with cancer receiving specialist palliative care: a retrospective analysis of medical records
Authors: Murphy M , Bennett K , Hughes C , Cadogan C A 
Published: April 2022

Introduction

Older adults (≥65 years) with cancer often have existing comorbidities requiring multiple medications (1). Optimising medications in palliative care requires clinicians to consider whether each medication is appropriate in relation to patients’ context, treatment goals and life expectancy. The reported prevalence of potentially inappropriate prescribing (PIP) in general palliative care settings ranges from 15 to 92% (2). However, the application of tools that are specific to populations with limited life expectancy has been lacking in previous research (2).

Aim

To describe and assess the appropriateness of prescribing practices for older adults with cancer in the last seven days of life in an inpatient palliative care setting.

Methods

This was a retrospective observational study of medical records for older adults (≥65 years) with cancer who received inpatient specialist palliative care services in a hospice setting in Ireland in the final week of life over a two-year period. Data were extracted relating to patient demographics and prescribed medications using an electronic pro-forma. Medication appropriateness was assessed using the following tools: STOPPFrail (Version 2; consists of 25 deprescribing criteria for use in frail older adults with limited life expectancy), the OncPal deprescribing guideline (consists of eight medication classes for deprescribing in palliative patients with cancer) and criteria for identifying Potentially Inappropriate Prescribing in older adults with Cancer receiving Palliative Care (PIP-CPC; consists of 24 criteria for identifying potentially inappropriate prescribing of medications for symptomatic relief in older adults with cancer). These tools were retrospectively applied to the extracted data by the lead researcher. Data were analysed (Stata, Version 15) using descriptive statistics, including means (standard deviation, SD), medians (inter-quartile range, IQR) and frequency and percentage.

Results

One hundred and eighty older adults with cancer were included in this study. The majority were male (60.6%) and the median age was 74 years (range 65-94 years). The most common primary cancer diagnoses affected the digestive organs (31.7%), respiratory and intrathoracic organs (18.8%) and male genital organs (10%). Almost all patients (94.5%) had at least one comorbid condition (median 3, IQR 2-5). The median number of medications increased from five (IQR 3-7) seven days before death, to 11 medications on the day of death (IQR 9-15). The most prevalent drug classes were opioids, antipsychotics, antispasmodics, benzodiazepines and paracetamol. More than half of patients had at least one PIP identified by the tools (n=97, 53.9%). The identified prevalence of PIP per tool in the patient cohort was: STOPPFrail V2 (20.6%), OncPal (12.7%), PIP-CPC (32.8%). However, several criteria could not be applied due to the absence of clinical information.

Conclusion

This study highlights that the number of medications prescribed to older adults with cancer increased as time to death approached, and that more than half of patients received at least one medication which was considered potentially inappropriate during their last week of life. The absence of electronic prescribing records and retrospective nature of the study limited the applicability of some criteria. Interventions are needed to optimise medication prescribing and use in palliative care settings.

References

(1) Sharma M, Loh KP, Nightingale G, Mohile SG, Holmes HM. Polypharmacy and potentially inappropriate medication use in geriatric oncology. J Geriatr Oncol. 2016;7(5):346-53.

(2) Cadogan CA, Murphy M, Boland M, Bennett K, McLean S, Hughes C. Prescribing practices, patterns, and potential harms in patients receiving palliative care: A systematic scoping review. Expl Res Clinic Soc Pharm. 2021;1(3):100050.