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Updated: Aug 25, 2025
Evaluating the Effectiveness of Cancer Drug Sensitization In Vitro and In Vivo
Published on: February 6, 2015
The feasibility and effects of a pharmacological treatment algorithm for cancer patients with terminal dyspnea:
Masanori Mori1, Takashi Yamaguchi2, Kozue Suzuki3
1Seirei Mikatahara General Hospital, Hamamatsu, Japan.
Background:
How clinicians treat patients with terminal dyspnea widely varies, which could hamper quality care. We visualized comprehensive pharmacological treatment delivered by palliative care physicians.
Aim:
To examine adherence to a comprehensive pharmacological treatment algorithm for patients with terminal dyspnea, and to explore its outcomes during 48 h.
Design:
A multicenter cohort study at five sites (February 2020 to June 2021).
Setting/Participants:
We prospectively enrolled consecutive patients with advanced cancer, Eastern Cooperative Oncology Group performance status 3-4, and moderate/severe dyspnea. Participating palliative care physicians initiated algorithm-based treatment. The primary outcome was the proportion of adherence to the treatment algorithm over 24 h (predefined goal, 70%). We evaluated the adherence, goal achievement, and dyspnea level with a numerical rating scale (NRS), as well as adverse events over 48 h.
Results:
All 108 patients received algorithm-based pharmacological treatment. Among 96 and 87 patients who were alive at 24 and 48 h, respectively, 96 (100%; 95% confidence interval [CI] = 96%-100%) and 82 (94%; 95%CI = 87%-98%) continued to receive the algorithm treatment, respectively, and 66 (69%; 95%CI = 59%-77%) and 64 (74%; 95%CI = 63%-82%) achieved the treatment goals, respectively. Using a complete case analysis with paired t-tests, mean dyspnea NRS scores significantly reduced from 7.3 (standard error, 0.2) at the baseline to 4.9 (0.3) at 24 h (n = 72; p < 0.001), and 7.2 (0.3) at the baseline to 4.6 (0.4) at 48 h (n = 55; p < 0.001). Most adverse events were mild to moderate.
Conclusions:
The comprehensive pharmacological treatment algorithm was feasible, and the study data supports its preliminary efficacy and safety. The use of this algorithm may help clinicians improve care for patients with terminal dyspnea.
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