5-EPIFAT trial protocol: a multi-center, randomized, placebo-controlled trial of the efficacy of pharmacotherapy for fatigue using methylphenidate, bupropion, ginseng, and amantadine in advanced cancer patients on active treatment.

BACKGROUND: Cancer-related fatigue (CRF) is still undertreated in most patients, as evidence for pharmacological treatments is limited and conflicting. Also, the efficacy of the pharmacological agents relative to each other is still unclear. Therefore, medications that may potentially contribute to improving CRF will be investigated in this head-to-head trial. Our main objective is to compare the efficacy of methylphenidate vs. bupropion vs. ginseng vs. amantadine vs. placebo in patients with advanced cancer. METHODS: The 5-EPIFAT study is a 5-arm, randomized, multi-blind, placebo-controlled, multicenter trial that will use a parallel-group design with an equal allocation ratio comparing the efficacy and safety of four medications (Methylphenidate vs. Bupropion vs. Ginseng vs. Amantadine) versus placebo for management of CRF. We will recruit 255 adult patients with advanced cancer who experience fatigue intensity ≥ 4 based on a 0-10 scale. The study period includes a 4-week intervention and a 4-week follow-up with repeated measurements over time. The primary outcome is the cancer-related fatigue level over time, which will be measured by the functional assessment of chronic illness therapy-fatigue (FACIT-F) scale. To evaluate safety, the secondary outcome is the symptomatic adverse events, which will be assessed using the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events in cancer clinical trials (PRO-CTCAE). Also, a subgroup analysis based on a decision tree-based machine learning algorithm will be employed for the clinical prediction of different agents in homogeneous subgroups. DISCUSSION: The findings of the 5-EPIFAT trial could be helpful to guide clinical decision-making, personalization treatment approach, design of future trials, as well as the development of CRF management guidelines. TRIAL REGISTRATION: IRCT.ir IRCT20150302021307N6. Registered on 13 May 2023.

A wide range of missing imputation approaches in longitudinal data: a simulation study and real data analysis.

BACKGROUND: Missing data is a pervasive problem in longitudinal data analysis. Several single-imputation (SI) and multiple-imputation (MI) approaches have been proposed to address this issue. In this study, for the first time, the function of the longitudinal regression tree algorithm as a non-parametric method after imputing missing data using SI and MI was investigated using simulated and real data. METHOD: Using different simulation scenarios derived from a real data set, we compared the performance of cross, trajectory mean, interpolation, copy-mean, and MI methods (27 approaches) to impute missing longitudinal data using parametric and non-parametric longitudinal models and the performance of the methods was assessed in real data. The real data included 3,645 participants older than 18 years within six waves obtained from the longitudinal Tehran cardiometabolic genetic study (TCGS). The data modeling was conducted using systolic and diastolic blood pressure (SBP/DBP) as the outcome variables and included predictor variables such as age, gender, and BMI. The efficiency of imputation approaches was compared using mean squared error (MSE), root-mean-squared error (RMSE), median absolute deviation (MAD), deviance, and Akaike information criteria (AIC). RESULTS: The longitudinal regression tree algorithm outperformed based on the criteria such as MSE, RMSE, and MAD than the linear mixed-effects model (LMM) for analyzing the TCGS and simulated data using the missing at random (MAR) mechanism. Overall, based on fitting the non-parametric model, the performance of the 27 imputation approaches was nearly similar. However, the SI traj-mean method improved performance compared with other imputation approaches. CONCLUSION: Both SI and MI approaches performed better using the longitudinal regression tree algorithm compared with the parametric longitudinal models. Based on the results from both the real and simulated data, we recommend that researchers use the traj-mean method for imputing missing values of longitudinal data. Choosing the imputation method with the best performance is widely dependent on the models of interest and the data structure.

Determining massage dose-response to improve cancer-related symptom cluster of pain, fatigue, and sleep disturbance: A 7-arm randomized trial in palliative cancer care.

BACKGROUND: The efficacy of various massage doses in palliative cancer care settings is still debated, and no specific protocol is available. AIM: Evaluating response to various massage doses for symptom cluster of pain-fatigue-sleep. DESIGN: A 7-arm randomized-controlled trial with weekly massage for 4 weeks depending on the prescribed dose (15-, 30-, or 60-min; 2× or 3×/week) and a 4-week follow-up. The intensities of pain, fatigue, and sleep disturbance were measured using a 0-10 scale at nine-timepoint; baseline, weekly during the intervention, and the follow-up period. Then, the mean scores of the three symptoms were calculated as the symptom cluster intensity at each timepoint. IRCT.ir IRCT20150302021307N5. SETTING/PARTICIPANTS: Adults with cancer (n = 273) who reported all three symptoms at three oncology centers in Iran. RESULTS: The odds of clinical improvement (at least 30% reduction in symptom cluster intensity from baseline) increased with dose-escalation significantly [(OR = 17.37; 95% CI = 3.87-77.90 for 60-min doses); (OR = 11.71; 95% CI = 2.60-52.69, for 30-min doses); (OR = 4.36; 95% CI = 0.94-20.32, for 15-min doses)]. The effect durability was significantly shorter at 15-min doses compared to 30- and 60-min doses. The odds of improvement for doses 3×/week was not significant compared to doses 2×/week (OR = 12.27 vs OR = 8.34); however, the effect durability for doses 3×/week was significantly higher. CONCLUSIONS: The findings indicated that dose-escalation increases the efficacy of massage for the pain-fatigue-sleep symptom cluster. Although the 60-min doses were found to be more effective, the 30-min doses can be considered more practical because they are less costly and time-consuming. Our findings can be helpful to develop massage guidelines in palliative care settings. TRIAL REGISTRATION: Iranian Registry of Clinical Trials, IRCT20150302021307N5.

The association between different predictive biomarkers and mortality of COVID-19.

Background: Immunocompromised individuals are expected to be more prone to severe diseases and, subsequently, death. Genetic disorders and polymorphisms in genes involved in the immune system, such as human leukocyte antigen (HLA), inflammatory cytokines, and killer-cell immunoglobulin-like receptors, can be involved in the immune system's response to various pathogens. In the current survey, the data were received from the world health organization, collected around the world. Results: Spearman's coefficient correlation test for evaluating the relationship between the Daily Death Rates (DDR) and immunological variables showed a statistically significant correlation between the DDR and all immunological variables except TNFa857T, TNFa863A IL2330G, and IL2166T (P < 0.001). Also, there was a statistically significant correlation between the DDR and some HLA markers. Conclusion: This meta-analysis study shows that predictive biomarkers and mortality of COVID-19 are associated with HLA markers. However, these results should be confirmed in a more structured agreement. It is worth noting that the design of new studies should consider potential diseases with poor prognoses because they are related to these immune genetic markers. Supplementary Information: The online version contains supplementary material available at 10.1186/s42269-022-00844-7.

A randomized trial of comparing video telecare education vs. in-person education on dietary regimen compliance in patients with type 2 diabetes mellitus: a support for clinical telehealth Providers.

BACKGROUND: Compliance to dietary recommendations by patients is the most difficult part of diabetes management. The nature of any educational method is to increase patients' awareness. But the question is, what is the effect of each method and for this purpose a comparative method should be considered. Therefore, this study was conducted to compare the effects of in-person education versus video tele-education on dietary regimen compliance in patients with T2DM. METHODS: In this trial, 378 patients with type 2 diabetes mellitus (T2DM) were random allocated into video tele-education, in-person education and control groups. The patients' weight and biochemical parameters were measured before educational programs and three-month later. RESULTS: The mean changes of patients' weight, glycemic parameters, and Lipid profiles decreased more in the two educational groups than the control group in a three-month period. There were no significant differences in the all study variables between the in-person and video education groups in post interventions except Total Cholesterol (TC). The pre- and post-intervention changes in the weight, TC, hemoglobin A1c, Triglyceride, and Very Low-density Lipoprotein Cholesterol were significant in both in-person group and video group. None of the educational programs had a significant impact on the Fasting blood sugar, Low-Density Lipoprotein Cholesterol, and High-Density Lipoprotein Cholesterol. DISCUSSION: Video tele-education was just as effective as in-person educational method on dietary regimen compliance among patients with T2DM in a three-month period. Therefore, it is recommended to use video tele-education in combination with or as an alternative to the in-person education method. This study provides support for diabetes educator. TRIAL REGISTRATION: This investigation was registered in the Iranian Registry of Clinical Trials Center ( IRCT20150302021307N4 ).

Application of Bayesian Decision Tree in Hematology Research: Differential Diagnosis of ß-Thalassemia Trait from Iron Deficiency Anemia.

OBJECTIVE: Several discriminating techniques have been proposed to discriminate between ß-thalassemia trait (ßTT) and iron deficiency anemia (IDA). These discrimination techniques are essential clinically, but they are challenging and typically difficult. This study is the first application of the Bayesian tree-based method for differential diagnosis of ßTT from IDA. METHOD: This cross-sectional study included 907 patients with ages over 18 years old and a mean (±SD) age of 25 ± 16.1 with either ßTT or IDA. Hematological parameters were measured using a Sysmex KX-21 automated hematology analyzer. Bayesian Logit Treed (BLTREED) and Classification and Regression Trees (CART) were implemented to discriminate ßTT from IDA based on the hematological parameters. RESULTS: This study proposes an automatic detection model of beta-thalassemia carriers based on a Bayesian tree-based method. The BLTREED model and CART showed that mean corpuscular volume (MCV) was the main predictor in diagnostic discrimination. According to the test dataset, CART indicated higher sensitivity and negative predictive value than BLTREED for differential diagnosis of ßTT from IDA. However, the CART algorithm had a high false-positive rate. Overall, the BLTREED model showed better performance concerning the area under the curve (AUC). CONCLUSIONS: The BLTREED model showed excellent diagnostic accuracy for differentiating ßTT from IDA. In addition, understanding tree-based methods are easy and do not need statistical experience. Thus, it can help physicians in making the right clinical decision. So, the proposed model could support medical decisions in the differential diagnosis of ßTT from IDA to avoid much more expensive, time-consuming laboratory tests, especially in countries with limited recourses or poor health services.

Diagnostic performance of classification trees and hematological functions in hematologic disorders: an application of multidimensional scaling and cluster analysis.

BACKGROUND: Several hematological indices have been already proposed to discriminate between iron deficiency anemia (IDA) and ß-thalassemia trait (ßTT). This study compared the diagnostic performance of different hematological discrimination indices with decision trees and support vector machines, so as to discriminate IDA from ßTT using multidimensional scaling and cluster analysis. In addition, decision trees were used to determine the diagnostic classification scheme of patients. METHODS: Consisting of 1178 patients with hypochromic microcytic anemia (708 patients with ßTT and 470 patients with IDA), this cross-sectional study compared the diagnostic performance of 43 hematological discrimination indices with classification tree algorithms and support vector machines in order to discriminate IDA from ßTT. Moreover, multidimensional scaling and cluster analysis were used to identify the homogeneous subgroups of discrimination methods with similar performance. RESULTS: All the classification tree algorithms except the LOTUS tree algorithm showed acceptable accuracy measures for discrimination between IDA and ßTT in comparison with other hematological discrimination indices. The results indicated that the CRUISE and C5.0 tree algorithms had better diagnostic performance and efficiency among other discrimination methods. Moreover, the AUC of CRUISE and C5.0 tree algorithms indicated more precise classification with values of 0.940 and 0.999, indicating excellent diagnostic accuracy of such models. Moreover, the CRUISE and C5.0 tree algorithms showed that mean corpuscular volume can be considered as the main variable in discrimination between IDA and ßTT. CONCLUSIONS: CRUISE and C5.0 tree algorithms as powerful methods in data mining techniques can be used to develop accurate differential methods along with other laboratory parameters for the discrimination of IDA and ßTT. In addition, the multidimensional scaling method and cluster analysis can be considered as the most appropriate techniques to determine the discrimination indices with similar performance for future hematological studies.

Diagnostic performance of hematological discrimination indices to discriminate between ßeta thalassemia trait and iron deficiency anemia and using cluster analysis: Introducing two new indices tested in Iranian population.

Although the discrimination between ß-thalassemia trait (ßTT) and Iron deficiency anemia (IDA) is important clinically, but it is challenging and normally difficult; so if a patient with IDA is diagnosed as ßTT, then it is deprived of iron therapy. This study purpose was to evaluate the 26 different discriminating indices diagnostic function in patients with microcytic anemia by using accuracy measures, and also recommending two distinct new discriminating indices as well. In this study, 907 patients were enrolled with the ages over 18-year-old with either ßTT or IDA. Twenty-six discrimination indices diagnostic performance presented in earlier studies, and two new indices were introduced in this study (CRUISE index and index26) in order to evaluate the differential between ßTT and IDA by using accuracy measures. 537 (59%) patients with ßTT (299 (56%) women, and 238 (44%) men), and also 370 (41%) patients with IDA (293 (79%) women, and 77 (21%) men) were participated in this study for evaluating the 28 discrimination indices diagnostic performance. Two new introduced indices (CRUISE index and index26) have better performance than some discrimination indices. Indices with the amount of AUC higher than 0.8 had very appropriate diagnostic accuracy in discrimination between ßTT and IDA, and also CRUISE index has good diagnostic accuracy, too. The present study was also the first cluster analysis application in order to identify the homogeneous subgroups of different indices with similar diagnostic function. In addition, new indices that offered in this study have presented a relatively closed diagnostic performance by using cluster analysis for the different indices described in earlier studies. Thus, we suggest the using of cluster analysis in order to determine differential indices with similar diagnostic performances.