METHODS: Pubmed, Cochrane Central, PsycINFO, EMBASE, and WoS were searched from inception to April 2023. Randomised controlled trials (RCTs) that evaluated effects of mHealth apps on primary outcomes OAM adherence and symptom burden were included. Two reviewers independently assessed risk-of-bias using Cochrane Risk-of-Bias version 2 and extracted the data. Quality of evidence was assessed using GRADE. The protocol was registered in PROSPERO (CRD42023406024).
RESULTS: Four RCTs involving 806 patients with cancer met the eligibility criteria. mHealth apps features included a combinations of symptom reporting, medication reminder, automated alert to care team, OAM and side effect information, one study implemented structured follow-up by a nurse. The intervention group showed no significant difference in OAM adherence (relative ratio 1.20; 95% CI 1.00 to 1.43), but significantly improved symptoms to OAMs with a lower standardised mean symptom burden score of 0.49 (SMD - 0.49; 95% CI - 0.93 to - 0.06), and a 25% lower risk of grade 3 or 4 toxicity (risk ratio 0.75; 95% CI 0.58 to 0.95) compared to usual care.
CONCLUSION: These findings suggest a potential role for mHealth app in managing OAM side effect. Further research should explore the role of AI-guided algorithmic pathways on the interactive features of mHealth apps.
Methods: A systematic literature search was performed in 5 databases for articles published between 2002 and 2021. Studies that compared adherence enhancing interventions implemented by healthcare professionals with a comparison group were included. Relevant data on study characteristics were extracted. Medication adherence and clinical outcomes between intervention and control arms were compared.
Results: Nine studies were included in two randomised controlled trials, four cohort studies, and three before-and-after comparison studies. All the included studies incorporated complex interventions, including intensive education or consultation with pharmacists, nurses or multidisciplinary team, in combination with one or more other strategies such as structured follow-up, written materials or video, psychotherapy, medication reminder or treatment diary, with the overall goal of monitoring and improving TKI adherence. Most (7 out of 9) studies demonstrated significantly better adherence to TKIs in the intervention group than the comparison group. The relative proportion of participants who adhered to TKIs ranged from 1.22 to 2.42. The improvement in the rate of TKI doses taken/received ranged from 1.5% to 7.1%. Only one study showed a significant association between intervention and clinical outcomes, with a 22.6% higher major molecular response rate and improvement in 6 out of 20 subscales of health-related quality-of-life.
Conclusion: Complex interventions delivered by healthcare professionals showed improvement in adherence to TKIs in CML patients. Further studies are required to clarify the cost-effectiveness of adherence-enhancing interventions.
METHODS: A parallel RCT was conducted in two hospitals in Malaysia, where 129 CML patients were randomised to MMS or control (usual care) groups using a stratified 1:1 block randomisation method. The 6-month MMS included three face-to-face medication use reviews, CML and TKI-related education, two follow-up telephone conversations, a printed information booklet and two adherence aids. Medication adherence (primary outcome), molecular responses and health-related quality of life (HRQoL) scores were assessed at baseline, 6th and 12th month. Medication adherence and HRQoL were assessed using medication possession ratio and the European Organisation for Research and Treatment in Cancer questionnaire (EORTC_QLQ30_CML24) respectively.
RESULTS: The MMS group (n = 65) showed significantly higher adherence to TKIs than the control group (n = 64) at 6th month (81.5% vs 56.3%; p = 0.002), but not at 12th month (72.6% vs 60.3%; p = 0.147). In addition, a significantly higher proportion of participants in the MMS group achieved major molecular response at 6th month (58.5% vs 35.9%; p = 0.010), but not at 12th month (66.2% vs 51.6%; p = 0.092). Significant deep molecular response was also obtained at 12th month (24.6% vs 10.9%; p = 0.042). Six out of 20 subscales of EORTC-QLQ30-CML24 were significantly better in the MMS group.
CONCLUSIONS: The MMS improved CML patients' adherence to TKI as well as achieved better clinical outcomes.
TRIAL REGISTRATION: Clinicaltrial.gov (ID: NCT03090477).
MATERIALS AND METHODS: In the present study, we examined the adjuvant effect of polymyxin B on the antibacterial activity of curcumin-mediated aPDT against P. aeruginosa. P. aeruginosa was treated with curcumin in the presence of 0.1-0.5 mg/L polymyxin B and irradiated by blue LED light (10 J/cm2). Bacterial cultures treated with curcumin alone served as controls. Colony forming units (CFU) were counted and the viability of P. aeruginosa was calculated after aPDT treatment. The possible underlying mechanisms for the enhanced killing effects were also explored.
RESULTS: The killing effects of curcumin-mediated aPDT against P. aeruginosa was significantly enhanced by polymyxin B (over 2-log reductions). Moreover, it was also observed that addition of polymyxin B in the curcumin-mediated aPDT led to the apparent bacterial membrane damage with increased leakage of cytoplasmic contents and extensive DNA and protein degradation.
DISCUSSION: The photodynamic action of curcumin against P. aeruginosa could be significantly enhanced by the FDA-approved drug polymyxin B. Our results highlight the potential of introducing polymyxin B to enhance the effects of aPDT treatment against gram-negative skin infections, in particular, P. aeruginosa.
METHODS: This study included participants from the intervention arm of a randomised controlled trial which was conducted to evaluate the effects of pharmacist-led interventions on CML patients treated with TKIs. Participants were recruited and followed up in the haematology clinics of two hospitals in Malaysia from March 2017 to January 2019. A pharmacist identified DRPs and helped to resolve them. Patients were followed-up for six months, and their DRPs were assessed based on the Pharmaceutical Care Network Europe Classification for DRP v7.0. The identified DRPs, the pharmacist's interventions, and the acceptance and outcomes of the interventions were recorded. A Poisson multivariable regression model was used to analyse factors associated with the number of identified DRPs per participant.
RESULTS: A total of 198 DRPs were identified from 65 CML patients. The median number of DRPs per participants was 3 (interquartile range: 2, 4). Most participants (97%) had at least one DRP, which included adverse drug events (45.5%), treatment ineffectiveness (31.5%) and patients' treatment concerns or dissatisfaction (23%). The 228 causes of DRPs identified comprised the following: lack of disease or treatment information, or outcome monitoring (47.8%), inappropriate drug use processes (23.2%), inappropriate patient behaviour (19.9%), suboptimal drug selection (6.1%), suboptimal dose selection (2.6%) and logistic issues in dispensing (0.4%). The number of concomitant medications was significantly associated with the number of DRPs (adjusted Odds Ratio: 1.100; 95% CI: 1.005, 1.205; p = 0.040). Overall, 233 interventions were made. These included providing patient education on disease states or TKI-related side effects (75.1%) and recommending appropriate instructions for taking medications (7.7%). Of the 233 interventions, 94.4% were accepted and 83.7% were implemented by the prescriber or patient. A total of 154 DRPs (77.3%) were resolved.
CONCLUSIONS: The pharmacist-led interventions among CML patients managed to identify various DRPs, were well accepted by both TKI prescribers and patients, and had a high success rate of resolving the DRPs.
METHODS: This double-blind, randomized, placebo-controlled trial involved fifty subjects with sleep complaints. Subjects with a Pittsburgh Sleep Quality Index (PSQI) score between 6 and 15 were randomized to receive either IQP-AO-101 or placebo for 6 weeks, following a run-in period of one week. Sleep parameters were assessed at baseline and after 1, 4, and 6 weeks using the modified Athens Insomnia Scale (mAIS). Subjects were also instructed to wear an activity tracker and keep a sleep diary during the study. Other questionnaires administered were the Frankfurt Attention Inventory (FAIR-2) and the Profile of Mood States (POMS-65). Blood samples for safety laboratory parameters were taken before and at the end of the study.
RESULTS: After 6 weeks, subjects who consumed IQP-AO-101 reported significant improvements in mAIS scores compared with placebo, including mAIS total score (11.76 ± 6.85 vs 4.00 ± 4.80; p < 0.001); night parameters composite score (5.20 ± 3.80 vs 2.04 ± 3.16; p = 0.001); and day parameters composite score (6.56 ± 4.10 vs 1.96 ± 2.65; p < 0.001). All individual parameters (Items 1 to 8) were also significantly improved from baseline after 6 weeks of IQP-AO-101 intake. Analysis of variance with baseline values as covariates showed statistically significant improvements across all individual parameters for IQP-AO-101 when compared to placebo. The measurements using the activity tracker, sleep diary, FAIR-2, and POMS did not reveal any significant differences between groups. No adverse effects related to the intake of IQP-AO-101 were reported. Tolerability was rated as very good by all the subjects and by the investigator for all cases.
CONCLUSIONS: In this study, IQP-AO-101 was well tolerated and efficacious for promoting sleep and enhancing daytime performance in subjects with moderate sleep disturbances.
CLINICAL TRIAL REGISTRATION: This trial is registered with ClinicalTrials.gov, no. NCT03114696.