A multiphase study protocol of identifying, and predicting cancer-related symptom clusters: applying a mixed-method design and machine learning algorithms.

Objectives: In recent years, there has been increasing attention on the cluster approach to symptom management. Two significant challenges in the symptom cluster (SC) approach are identifying and predicting these clusters. This multiphase protocol aims to identify SCs in patients with advanced cancer as the primary objective, with the secondary objective of developing machine learning algorithms to predict SCs identified in the first phase. Methods: The 2-MIXIP study consists of two main phases. The first phase involves identifying SCs, and the second phase focuses on developing predictive algorithms for the identified SCs. The identification of SCs involves a parallel mixed-method design (quantitative and qualitative). Quantitative and qualitative methods are conducted simultaneously and given equal importance. The data are collected and analyzed independently before being integrated. The quantitative part is conducted using a descriptive-analytical method. The qualitative analysis is conducted using a content analysis approach. Then, the identified SCs from both parts are integrated to determine the final clusters and use them in the second phase. In the second phase, we employ a tree-based machine learning method to create predictive algorithms for SCs using key demographic and clinical patient characteristics. Conclusion: The findings of the 2-MIXIP study can help manage cancer patients' symptoms more effectively and enhance clinical decision-making by using SCs prediction. Furthermore, the results of this study can provide guidance for clinical trials aimed at managing symptoms.

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.

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.

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 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.