Published online Mar 24, 2025. doi: 10.5306/wjco.v16.i3.101705
Revised: November 23, 2024
Accepted: January 7, 2025
Published online: March 24, 2025
Processing time: 110 Days and 6.6 Hours
Older patients are more likely to have a poor performance status and comor
To investigated the role of palliative radiotherapy in older patients and patients who were expected to demonstrate a therapeutic effect.
From February 2019 to February 2022, 33 patients aged ≥ 80 years underwent palliative radiotherapy. The prognosis in palliative care study predictor (PiPS), palliative prognostic index (PPI), and delirium-palliative prognostic score (D-PaP) models were used for prognosis prediction. D-PaP scores calculated according to the doctor's prediction of clinical prediction of survival (CPS) were excluded and then analyzed for comparison. Radiation was prescribed at a dose of 2.5-7 Gy per fraction, up to a median of 39 Gy10 (range, 28-75 Gy10).
The median follow-up was 2.4 months (range, 0.2-27.5 months), and 28 patients (84.8%) showed subjective symptom improvements following treatment. The 2- and 6-month survival rates of all patients were 91.5% and 91.5%, respectively. According to regression analysis, the performance status index, symptom type, and radiation dose all showed no significant correlation with the treatment re
This study shows that the prognosis prediction model used in palliative care can be used to identify patients suitable for treatment.
Core Tip: This is a retrospective study to investigate the role of palliative radiotherapy in older patients and patients who were expected to demonstrate a great therapeutic effect. The prognosis in palliative care study predictor, palliative prognostic index, and delirium-palliative prognostic score models were used for prognosis prediction. Most of patients showed subjective symptom improvements following treatment. The prognosis prediction model showed good correlation with survival. In order to increase the therapeutic effectiveness in palliative radiotherapy, it is necessary to assess a patient's exact prognosis and select appropriate patients accordingly.
