BackgroundThe incidence of cancer pain increases in discharged patients because of discontinued standard treatments and reductions in medication adherence. Motivated by the need for better pain management in discharged patients, we developed a mobile phone app (Pain Guard) to provide continuous treatment information and feedback to discharged cancer patients suffering from pain.ObjectiveThe aim was to design, construct, and test the Pain Guard app in patients managing cancer pain, evaluate the total remission rate of pain and the improvement in quality of life (QoL) to improve pain management for cancer pain patients, and assess patient acceptance of the app.MethodsThis randomized controlled double-arm study involved 58 patients with cancer pain symptoms. Participants were randomly assigned to a group receiving care through the Pain Guard app (n=31) or to a control group (n=27) who received only traditional pharmaceutical care. In a pretest, participants were rated using a baseline cancer pain assessment and QoL evaluation. During treatment, the consumption levels of analgesic drugs were recorded every week. After a 4-week study period, another round of cancer pain assessment and QoL evaluation was conducted. The system’s usability, feasibility, app compliance, and satisfaction were also assessed. Our primary outcome was remission rate of pain, and secondary outcomes were medication adherence, improvements in QoL, frequency of breakthrough cancer pain (BTcP), incidence of adverse reactions, and satisfaction of patients.ResultsAll participants (N=58) successfully completed the study. There were no significant differences in baseline pain scores or baseline QoL scores between groups. At the end of the study, the rate of pain remission in the trial group was significantly higher than that in the control group (P<.001). The frequency of BTcP in the app group was considerably lower than that in the control group (P<.001). The rate of medication adherence in the trial group was considerably higher than that in the control group (P<.001). Improvements in global QoL scores in the trial group were also significantly higher than those in the control group (P<.001). The incidence of adverse reactions in the trial group (7/31) was lower than that in the control group (12/27), especially constipation, with significant differences (P=.01). The 31 participants in the trial group completed a satisfaction survey regarding Pain Guard: 23 (74%) indicated that they were satisfied with receiving pharmaceutical care by Pain Guard, 5 (16%) indicated that they were somewhat satisfied, 2 (6%) indicated neutral feelings, and 1 (3%) indicated that they were somewhat dissatisfied; no participants indicated that they were very dissatisfied.ConclusionsPain Guard was effective for the management of pain in discharged patients with cancer pain, and its operability was effective and easily accepted by patients.Trial RegistrationChinese Clinical Trials Registry ChiCTR1800016066; http://www.chictr.org.cn/showproj.aspx?proj=27153

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From the perspective of the Chinese medical system, imatinib is likely to be more cost effective than dasatinib and nilotinib for patients who were first diagnosed with CML-CP.

AimsNirmatrelvir is an antiviral drug with a novel mechanism of action, targeting the 3‐CL protease, and is used in the treatment of COVID‐19. However, the potential side effects have not yet been fully studied. The aim of this study was to identify potential safety signals of nirmatrelvir by analysing post‐marketing safety data based on the largest publicly available worldwide pharmacovigilance database.MethodsWe analysed nirmatrelvir adverse events to identify and characterize relevant safety signals based on the FDA Adverse Event Reporting System database in 2022. The case/non‐case approach was used to estimate the reporting odds ratio (ROR) and information component (IC) with relevant confidence intervals (95% CI) for adverse events (AEs) that numbered 4 or more.ResultsA total of 26 846 cases were included. Disease recurrence (ROR [95% CI] = 413.2 [395.6–431.59]), dysgeusia (ROR [95% CI] = 110.84 [106.04–115.85]), anosmia (ROR [95% CI] = 15.21 [12.76–18.11]), ageusia (ROR [95% CI] = 9.80 [8.50–11.3]) and urticaria (ROR [95% CI] = 1.91 [1.69–2.17]) were the main safety signals. In addition, abdominal pain upper and skin toxicity were two specific safety signals of nirmatrelvir. In the pregnant population, there was a significant increased ROR for life‐threatening conditions (ROR [95% CI] = 8.00 [1.77–36.20]).ConclusionsOur study identified that the main and specific safety signals of nirmatrelvir were disease recurrence, dysgeusia, abdominal pain upper and skin toxicity. Clinicians and pharmacists should be vigilant of these AEs, although differentiating between COVID‐19 symptoms and AEs can be challenging. Notably, a potential safety concern of nirmatrelvir should be a warning based on a small number of events in the pregnant population. However, the available data are insufficient, and further continued pharmacovigilance and surveillance is needed to fully understand this issue.

BACKGROUND Cancer pain is a significant public health issue. Mobile health offers improved and cost-effective care to people with cancer pain. However, the efficiency of engagement strategies and modules of this technology need to be reviewed and standardized according to expert perspectives. The use of applications (apps) for cancer pain management has increased over recent years. However, evidence regarding the efficacy and safety of these apps remains lacking. This study used the modified Delphi process on the design of cancer pain management apps. OBJECTIVE The study aimed to design the most agreed-upon modules for cancer pain management mobile apps. METHODS This study recruited experts in the domain of cancer pain management and applied a modified Delphi method to design the most relevant app modules. We used the positive coefficient and authority of expert indexes, such as the degree of coordination with expert opinions and other modules to test the reliability of the consultation. Cronbach’s α coefficient, content validity index (CVI), were used for data analysis. RESULTS A total of 23 experts with a mean age of 42.3 years (SD 5.7) consented to participate in the study. All of them had worked more than 10 years in the cancer pain management field. Overall, five app modules were generated. The Cronbach’s a coefficient was 0.81 for the overall scale.The scale-level CVI was 0.78. CONCLUSIONS This study is the first in China to recruit a local panel of experts from the cancer pain management field. We used an iterative process to combine the experts’ opinions into a group consensus. The results of this study could benefit developers of health apps and inform future decision making on cancer pain management.