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

Utilizing Perioperative Variation Trends of Circulating Tumor Cells and Tumor Pathological Characteristics as a Combined Relapse Prediction Model for Resectable Non-Small Cell Patients - a Prospective Clinical Feasibility Trial

Status
Recruiting
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT06262386
Enrollment
358
Registered
2024-02-16
Start date
2023-08-01
Completion date
2028-07-31
Last updated
2024-02-16

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Lung Cancer, Relapse/Recurrence

Keywords

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

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.

Detailed description

For patients with resectable lung cancer, anatomic resection alongside mediastinal lymph node dissection is pivotal in removing all tumor tissue visible on imaging from the patient's body. Despite these efforts, early relapse remains a significant issue. Literature review shows that the early relapse rate varies between 8 to 10%, potentially due to undetectable occult metastasis by imaging modalities, suggesting the presence of minimal residual disease or tumor cells evading the primary site. Limitations in imaging, such as the slice thickness in computed tomography (CT) scans, which range from 0.375 to 0.5 centimeters, can render tumors smaller than the slice thickness invisible. Similarly, tumors smaller than 0.5 cm may not accumulate sufficient F18-Deoxyglucose to be detectable in positron emission tomography (PET) scans. Additionally, tumor cells may migrate to extrapulmonary sites via lymphatic drainage or circulation. Survival studies have predominantly focused on the pathologic TNM stage, which aggregates different disease presentations with similar survival outcomes. However, the heterogeneity inherent in pathology may help in identifying patients prone to relapse. From a tumor biology perspective, tumor cells may detach from surrounding tissues, becoming more invasive and entering the bloodstream. Circulating tumor cells (CTCs) have been recognized early in cancer stages and are correlated with treatment response, tumor genetic alterations, and survival. Research has combined CT tumor size and CTCs in a malignancy prediction model for suspicious pulmonary lesions, highlighting that CTCs can rebound in patients experiencing early relapse, indicating occult metastases or minimal residual disease. Systemic adjuvant therapy is considered the best approach to minimize disease relapse in resectable lung cancer patients. Although many studies have sought to identify patients at risk of relapse to improve survival, the presence of intrapulmonary (N1) or mediastinal (N2) lymph node invasion significantly affects survival in non-small cell lung cancer patients. Even tumors smaller than 1 cm carry a risk of lymph node metastases, with respective risks for cT1a, cT1b, and cT1c tumors reported as 3.8%, 16.3%, and 19.6%. Therefore, patients with tumors larger than 1 cm are recommended adjuvant therapy due to the high risk of lymph node involvement. Adjuvant chemotherapy is advised for patients with stages 1b to 3a, showing a 5.4% survival benefit by the fifth postoperative year, although this benefit diminishes in subsequent years. This could be due to adjuvant therapy being administered based on the pathologic stage rather than the likelihood of relapse. Tumor heterogeneity might also influence the response to different therapeutic regimens. Molecular profiling of tumors has identified mutations predicting responses to targeted therapies and elucidated drug resistance mechanisms, offering more precise treatments and improving survival. Targeted and immune therapies have shown improved survival in specific tumor subgroups. This study aims to utilize trends in CTC variations as a screening tool to identify patients at risk of relapse and prescribe adjuvant therapy to evaluate the therapeutic efficacy and survival impact of CTCs.

Interventions

DRUGCisplatin based chemottherapy

adjuvant therapy for high risk patient

Sponsors

National Science and Technology Council
CollaboratorFED
Chang Gung Memorial Hospital
Lead SponsorOTHER

Study design

Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
OTHER
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
20 Years to 90 Years
Healthy volunteers
No

Inclusion criteria

1. Patients who presented with resectable disease ( Clinical stage 1a to 3a) 2. Patients who received tumor resection

Exclusion criteria

1. Pathologic stage greater than stage 3b or 4 2. Pathologic stage less than stage 1a1 3. Could not complete treatment course 4. Could not receive blood sampling for CTC (circulating tumor cell) or regular surveillance

Design outcomes

Primary

MeasureTime frameDescription
Accuracy of proposed relapse prediction modelfollow up in 3 month-interval1. 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
early relapse ratefollow up in 3 month-interval1. 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

Secondary

MeasureTime frameDescription
Overall surveivalfollow up in 3 month-intervalGoal: difference of overall survival among patients with relapse risk 1. treatment based on proposed relapse prediction model 2. calculate the overall survival 3. utilized historical cohort as historical control ( cohort that utilized to establish proposed relapse prediction model * treatment based on TNM stage * calculate the overall survival rate

Countries

Taiwan

Contacts

Primary ContactChing-Yang Wu
wu.chingyang@gmail.com+886975368204
Backup ContactChia-Tsun CH Hsieh
wisdom5000@gmail.com-886975366137

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026