Combined Relapse Prediction Model for Resectable Non-Small Cell Patients - a Prospective Clinical Feasibility Trial

NCT06262386 | Recruiting DMC

• 1 other identifier: 202202172B0
• Study Type: interventional
• Target: 358
• Locations: 1 country
• Sites: 1

Brief Summary

For patients with lung cancer who have undergone tumor resection, early relapse significantly impacts survival. However, there are currently no reliable screening or imaging tools available to identify patients at risk of early relapse. To address this clinical challenge, many studies have focused on understanding the clinicopathologic characteristics associated with an increased risk of early relapse. Despite these efforts, we can identify patients at risk but cannot pinpoint which individuals will actually experience early relapse. Studies on adjuvant therapy have shown improved survival in cases of more advanced disease but have not demonstrated a reduction in early relapse rates. In our preliminary analysis of previous study data, we observed that patients with a smaller reduction in circulating tumor cells (CTCs) within the first three days after surgery, followed by an increase on the third-day post-operation, are more likely to experience early relapse during regular monitoring. This pattern may be indicative of minimal residual disease. By combining trends in circulating tumor cell variations with pathologic characteristics, we aim to select patients for adjuvant therapy who are at high risk of developing early relapse. The objective of our study is to employ screening based on circulating tumor cell dynamics and pathologic features to identify patients likely to experience early relapse and to assess the effectiveness of adjuvant therapy in these cases.

Conditions

Lung Cancer; Relapse/Recurrence

Keywords

Circulating tumor cell; resectable non-small cell lung cancer; Early relapse

Outcome Measures

Primary Outcomes (2)

• Accuracy of proposed relapse prediction model

  1. Utilized the enrolled patients to testify proposed relapse prediction model 2. Calculated Positive prediction rate, Negative prediction rate, accuracy 3. Goal: high positive prediction rate, lower negative prediction rate, high accuracy

  follow up in 3 month-interval

• early relapse rate

  1. adjuvant therapy based on proposed relapse prediction model * calculate the early relapse rate (relapse within 3 years) 2. utilized historical cohort as historical control (cohort that utilized to establish proposed relapse prediction model * adjuvant therapy based on TNM stage * calculate the early relapse rate (relapse within 3 years) * follow up Chest CT/ CTC in 3-month interval

  follow up in 3 month-interval

Secondary Outcomes (1)

• Overall surveival

  follow up in 3 month-interval

Study Arms (1)

Patient at risk for disease relapse after surgery

EXPERIMENTAL

1. we utilized a relapse prediction model that combined perioperative variation trends of circulating tumor cells and pathologic characteristics that were collated with relapse 1. circulating tumor cell variation trend: difference between the CTC count on post-operation day 3 and day 1; difference between the CTC count on post-operation day 3 and post-operation 2. pathologic staging 0-1a/ 1b-4 2. patient with high relapse for relapse * Adjuvant was recommended as NCCN guidelines recommended

Drug: Cisplatin based chemottherapy

Interventions

Cisplatin based chemottherapy DRUG

adjuvant therapy for high risk patient

Patient at risk for disease relapse after surgery

Eligibility Criteria

• Age: 20 Years - 90 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Patients who presented with resectable disease ( Clinical stage 1a to 3a)
• Patients who received tumor resection

You may not qualify if:

• Pathologic stage greater than stage 3b or 4
• Pathologic stage less than stage 1a1
• Could not complete treatment course
• Could not receive blood sampling for CTC (circulating tumor cell) or regular surveillance

Sponsors & Collaborators

• Chang Gung Memorial Hospital: lead
• National Science and Technology Council: collaborator

Study Sites (1)

Ching-Yang Wu

Taoyuan, 333, Taiwan

RECRUITING

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MeSH Terms

Conditions

Lung Neoplasms; Recurrence; Neoplastic Cells, Circulating

Condition Hierarchy (Ancestors)

Respiratory Tract Neoplasms; Thoracic Neoplasms; Neoplasms by Site; Neoplasms; Lung Diseases; Respiratory Tract Diseases; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Neoplasm Metastasis; Neoplastic Processes

Study Officials

• Ching-Yang Wu

  Chang Gung Memorial Hospital

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Ching-Yang Wu

CONTACT

+886975368204; wu.chingyang@gmail.com

Chia-Tsun CH Hsieh

CONTACT

-886975366137; wisdom5000@gmail.com

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: OTHER
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: September 22, 2023
• First Posted: February 16, 2024
• Study Start: August 1, 2023
• Primary Completion (Estimated): July 31, 2028
• Study Completion (Estimated): July 31, 2028
• Last Updated: February 16, 2024

Record last verified: 2023-08

Locations

TW (1)