An interventional study of National Cheng Kung University Abdominal Muscle Group Medical Imaging Analysis Software in Search MeSH, sponsored by National Cheng-Kung University Hospital. Not yet recruiting at 1 site in Taiwan. Open to female participants aged 18 Years to 80 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2025-09-22.
Sponsored by National Cheng-Kung University Hospital · Not applicable, Interventional, and Other
The dosage of paclitaxel, an adjuvant chemotherapy agent for endometrial and ovarian cancer, is typically calculated based on the patient's body surface area (BSA). However, cancer patients with the same BSA may exhibit significant differences in body composition, which could influence the distribution pattern of paclitaxel in the body. These variations may lead to individual differences in drug tolerance and adverse effects. Such variability not only impacts the patient's treatment experience and quality of life but may also increase medical costs, including hospitalization, emergency department visits, and additional treatments required to manage chemotherapy-induced toxicities.
Our preliminary study results indicate that skeletal muscle area (SMA) and skeletal muscle index (SMI), as assessed through computed tomography (CT) imaging, are significantly associated with the incidence of Grade 3 or higher leukopenia or neutropenia following the first two cycles of chemotherapy in patients with endometrial cancer. Furthermore, the predictive accuracy of these CT-derived muscle measurements surpasses the clinical judgment made by physicians based on conventional treatment guidelines. Patients who develop Grade 3 or higher leukopenia or neutropenia during the first two cycles are more likely to experience more frequent occurrences of Grade 3 or higher chemotherapy-related adverse effects in subsequent treatment cycles.
However, no study has comprehensively investigated the relationship between body composition, chemotherapy dosing, and adverse effects. Therefore, this trial aims to examine the impact of body composition on chemotherapy dose adjustments and adverse effects. By utilizing body composition data extracted from abdominal CT imaging through this product, this study seeks to establish a risk stratification tool to assist physicians in treating patients with endometrial and ovarian cancer by providing a reference for chemotherapy dose reduction.
It is expected that through a precision chemotherapy strategy, the incidence of chemotherapy-related adverse effects can be reduced, thereby lowering medical resource expenditures incurred from managing these adverse effects, such as emergency department visits, hospitalizations, additional diagnostic tests, and supportive medication costs. Furthermore, this approach aims to improve patients' health-related quality of life and achieve a dual benefit of medical economic efficiency and clinical effectiveness.
Endometrial cancer ranks sixth in incidence among women worldwide and is rising, while ovarian cancer, though less common, remains the leading cause of gynecologic cancer mortality. Standard adjuvant chemotherapy for these malignancies includes paclitaxel (dose based on body surface area, BSA) and carboplatin (dose based on AUC). However, BSA-based dosing does not account for variations in body composition, which can significantly influence drug distribution, toxicity, and treatment efficacy.
Retrospective analysis of 124 endometrial cancer patients at National Cheng Kung University Hospital demonstrated that CT-derived skeletal muscle parameters (SMA, SMI) are significantly associated with grade ≥3 hematologic toxicities and outperform traditional clinical judgment for risk prediction. Patients experiencing severe hematologic toxicity within the first two cycles are more likely to experience repeated toxicities in subsequent cycles.
This trial integrates prospective randomized controlled trial (RCT) and retrospective target trial emulation.
Prospective RCT: 294 patients will be stratified by cancer stage and randomized 1:1 to intervention vs. control groups. The intervention group will undergo AI-assisted risk stratification based on preoperative CT body composition analysis, with high-risk patients receiving a 15% paclitaxel dose reduction from cycle 1. The control group will receive standard-of-care dosing adjustments based on clinical judgment.
Retrospective analysis: Patients diagnosed from 2012-2024 with available CT images and complete treatment records will be analyzed using propensity score methods to control for confounders.
Primary endpoint: incidence of grade ≥3 leukopenia or neutropenia within the first two cycles.
Secondary endpoints: chemotherapy cycle delay (>7 days), hospitalization rate, HRQoL (CIPN, EORTC-QoL), two-year PFS and OS, cost-effectiveness (ICER, VBP).
The trial hypothesizes that AI-guided dosing adjustments will reduce severe hematologic toxicity rates from 75% to 60% without compromising relative dose intensity (>85%), thereby achieving both clinical and economic benefits.
National Cheng-Kung University Hospital is the lead sponsor of 268 studies on the registry; 68 are open to participants now.
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Inclusion Criteria
Adequate hematologic parameters:
Adequate organ function:
1. Presence of other major diseases that may be exacerbated by chemotherapy (e.g., autoimmune diseases).
2. History of other malignancies within the past two years before trial enrollment, except for adequately treated non-melanoma skin cancer, stage 0 cervical carcinoma, or ductal carcinoma in situ of the breast.
3. Requirement for concurrent treatment of unrelated diseases during the trial period, including chemotherapy, radiotherapy, or investigational drugs.
4. Mental status deemed unsuitable for participation in the clinical trial. 5. Expected survival time of less than six months. 6. Poor-quality abdominal CT images, clearly attributable to the following causes:
Phase 2: Prospective Multicenter Clinical Trial The second phase will involve a prospective multicenter clinical trial, enrolling 294 patients with endometrial or ovarian cancer.Patients will be randomized into two groups (at least 147 per group): 1. AI-assisted group (treatment group): Preoperative CT imaging will be used to assess body composition and classify patients into high-risk or low-risk categories.Chemotherapy dosing will be adjusted accordingly to evaluate treatment-related adverse effects and dose modifications. 2. Non-AI-assisted group (control group): Patients will receive chemotherapy dosing adjustments based on standard clinical care practices.
Device: National Cheng Kung University Abdominal Muscle Group Medical Imaging Analysis Software
Control Group (Standard chemotherapy dose adjustment without AI)
Phase 2: The second phase will involve a prospective multicenter clinical trial, enrolling 294 patients with endometrial or ovarian cancer.Patients will be randomized into two groups (at least 147 per group): AI-assisted group (treatment group): Preoperative CT imaging will be used to assess body composition and classify patients into high-risk or low-risk categories.Chemotherapy dosing will be adjusted accordingly to evaluate treatment-related adverse effects and dose modifications. Non-AI-assisted group (control group): Patients will receive chemotherapy chemotherapy dosing adjustments based on standard clinical care.
The accuracy of predicting the risk of Grade 3 or higher leukopenia or neutropenia as an adverse effect in endometrial and ovarian cancer patients undergoing postoperative adjuvant chemotherapy (including Paclitaxel) during the first two treatment cycles
Statistical methods: 1. The primary endpoint is a categorical variable, representing the incidence rate of patients experiencing adverse effects. Chi-square test or Fisher's exact test will be used to compare the incidence of Grade 3 or higher chemotherapy-related adverse effects between the experimental group (AI-assisted dose adjustment) and the control group (dose adjustment based on standard clinical guidelines). 2. Considering the impact of adverse effects across treatment cycles, a Generalized Estimating Equation (GEE) analysis will be performed to assess the overall differences between groups. Analysis approach: An intent-to-treat (ITT) analysis will be conducted, including all randomized participants to minimize selection bias.
Time frame: 6 weeks
Secondary endpoints include: Chemotherapy cycle delay, admission rate, health-related quality of life, two-year survival rates (PFS, OS), and cost-effectiveness.
Chemotherapy Cycle Delay Description: % of patients with \>7-day delay in any chemo cycle (21 days/cycle). Time Frame: First two cycles Unit: % of participants Hospitalization Rate Description: % of patients hospitalized at least once during chemo. Time Frame: Up to 2 years Unit: % of participants HRQoL - CIPN Score Description: Change in CIPN score from baseline. Time Frame: Baseline, during chemo, 1-year follow-up Unit: Scale units (CIPN) HRQoL - EORTC-QoL Score Description: Change in EORTC-QoL global health status score. Time Frame: Baseline, during chemo, 1-year follow-up Unit: Scale units (EORTC-QoL) Progression-Free Survival (PFS) Description: Time from first chemo to progression or death. Time Frame: Up to 24 months Unit: Months Overall Survival (OS) Description: Time from first chemo to death from any cause. Time Frame: Up to 24 months Unit: Months Incremental Cost-Effectiveness Ratio (ICER) Description: Cost/QALY for AI-assisted vs. standard dosing. Time Frame: Up to 2 year
Time frame: 2 years
This study is not yet recruiting, as verified in Jul 2025. You cannot join it, but the record below documents what was studied.
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National Cheng-Kung University Hospital