Clinical trial NCT06573307: Hematological Dynamic Scores for Predicting Survival and Treatment Response for Advanced Gastric Cancer After Neoadjuvant Therapy
Official title: To Develop a Prognostic Model for Predicting Survival and Treatment Response for Advanced Gastric Cancer Patients After Neoadjuvant Therapy by Analyzing Hematological Markers Dynamic Load
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Gastric Cancer
Keywords: Gastric cancer
Neoadjuvant chemotherapy
inflammation
Oxidative stress
Treatment response
Risk stratification
Lead sponsor: Fujian Medical University
Sponsor class: OTHER
First posted: 2024-08-27
Enrollment: 442
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: OTHER
Sampling method: NON_PROBABILITY_SAMPLE
Study population: In this study, we retrospectively collected clinicopathologic data and hematological markers before Neoadjuvant therapy and surgery in AGC patients who had undergone Neoadjuvant therapy and received radical gastrectomy in five hospitals.

Brief summary: HMDLS, based on hematological markers, could effectively distinguish the long-term efficacy of AGC patients after NAT. The predictive performance of nomogram-HMDLS was better than ypTNM stage, achieving better prognostic stratification and tumor treatment response prediction.

Detailed description: In this research, we incorporated a total of 320 patients from the Union Hospital of Fujian Medical University to form the training cohort (TC). Additionally, we included 122 patients from four distinct medical centers to serve as the external validation cohort (EVC). The Hematological Marker Dynamic Load (ΔHMDL) was determined using the following formula: ΔHMDL = (HMDL pre-surgery - HMDL pre-NAT) / HMDL pre-NAT, where HMDL represents the hematological marker levels before surgery and before the initiation of Neoadjuvant Therapy (NAT), respectively.

Employing LASSO regression analysis, we identified the most influential and statistically significant ΔHMDL indicators. These were then utilized to compute the Hematological Marker Dynamic Load Score (HMDLS), defined as: HMDLS = Σ(LASSO coefficient \* ΔHMDL), where the summation encompasses the products of the LASSO-estimated coefficients and the corresponding ΔHMDL values.

Further, leveraging the outcomes of a multivariate COX regression analysis, we integrated clinical parameters with the HMDLS to formulate a predictive model, termed the Nomogram-HMDLS model. The efficacy of this model in terms of predictive accuracy, clinical utility, and calibration was meticulously assessed and confirmed through several metrics, including the concordance index (C-index), Receiver Operating Characteristic (ROC) curve analysis, decision curve analysis (DCA), and calibration curves.

Eligibility criteria: Inclusion Criteria:

* (1) AGC with clinical stage T2-4NxM0 (cT2-4NxM0) before NAT, (2) no history of other malignant tumors, distant metastases or invasion of adjacent organs, and (3) patients who underwent radical gastrectomy after receiving NAT.

Exclusion Criteria:

* (1) history of upper abdominal surgery (except for the laparoscopic cholecystectomy), (2) history of upper abdominal radiotherapy, (3) emergency surgery, or palliative surgery, (4) continuous use of medications such as anticoagulant, antiplatelet, and leukocyte-boosting drugs that significantly affect hematological markers during therapy, and (5) incomplete clinical and follow-up data.

Primary outcomes:
measure: 3-year OS
timeFrame: 3-year OS or 36 months
measure: 3-year DFS
timeFrame: 3 years DFS or 36 months
measure: Tumor Regression Grade
timeFrame: 3 years or 36 months
Secondary outcomes:
Other outcomes:
Locations:
city: Fuzhou
country: China
facility: Department of Gastric Surgery， Fujian Medical University Union Hospital
state: Fujian
Study officials:
affiliation: Fujian Medical University Union Hospital
name: Changming Huang
role: PRINCIPAL_INVESTIGATOR
References: