Combined Relapse Prediction Model for Resectable Non-Small Cell Patients - a Prospective Clinical Feasibility Trial
Ориентир для пациента и семьи
Простыми словами
Автоматическая сводка по структурированным данным реестра. Она помогает сориентироваться, но не заменяет официальный протокол или оценку врача.
- Что изучают
- В протоколе указаны: Cisplatin based chemottherapy.
- Кому может быть актуально
- Состояния в реестре: Lung Cancer, Relapse/Recurrence. Базовые параметры: 20 лет — 90 лет · Все.
- Что важно проверить
- Возраст, диагноз и пол — только базовые ориентиры. Предыдущее лечение, анализы и другие обязательные условия указаны ниже в критериях участия.
- Где проводится
- Тайвань
- Следующий шаг
- Сохраните исследование, покажите его лечащему врачу и уточните актуальный статус у исследовательского центра. Расходы, документы и поездка →
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Официальное название
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
Обзор
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.
Подробное описание
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.
Вмешательства
- Препарат Cisplatin based chemottherapy
adjuvant therapy for high risk patient
Первичные конечные точки
- Accuracy of proposed relapse prediction model [Срок оценки: follow up in 3 month-interval]
- early relapse rate [Срок оценки: follow up in 3 month-interval]
Вторичные конечные точки (1)
- Overall surveival [Срок оценки: follow up in 3 month-interval]
Критерии участия
Критерии включения
- Patients who presented with resectable disease ( Clinical stage 1a to 3a)
- Patients who received tumor resection
Критерии исключения
- 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
Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.
Здоровые добровольцы: Нет
Дизайн исследования
- Распределение
- Не применимо
- Модель
- Одна группа
- Маскирование
- Открытое
- Основная цель
- Другое
Центры проведения
Тайвань · 1 центр
- Ching-Yang Wu — Taoyuan City
Публикации
- Wu CY, Fu JY, Wu CF, Liu YH, Hsieh MJ, Wu YC, Yang CT, Tsai YH. Pathologic Stage of Nonsmall Cell Lung Cancer Patients Presenting as Resectable Cases After Neoadjuvant Therapy Did Not Predict the Prognosis. Medicine (Baltimore). 2015 Oct;94(40):1. doi: 10.1097/MD.0000000000001700. PMID 26448022
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- Sun F, Xi J, Zhan C, Yang X, Wang L, Shi Y, Jiang W, Wang Q. Ground glass opacities: Imaging, pathology, and gene mutations. J Thorac Cardiovasc Surg. 2018 Aug;156(2):808-813. doi: 10.1016/j.jtcvs.2018.02.110. Epub 2018 Apr 13. PMID 29753514
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- Dahlbom M, Hoffman EJ, Hoh CK, Schiepers C, Rosenqvist G, Hawkins RA, Phelps ME. Whole-body positron emission tomography: Part I. Methods and performance characteristics. J Nucl Med. 1992 Jun;33(6):1191-9. PMID 1597738
- Nolop KB, Rhodes CG, Brudin LH, Beaney RP, Krausz T, Jones T, Hughes JM. Glucose utilization in vivo by human pulmonary neoplasms. Cancer. 1987 Dec 1;60(11):2682-9. doi: 10.1002/1097-0142(19871201)60:113.0.co;2-h. PMID 3499969
- Brown RS, Leung JY, Kison PV, Zasadny KR, Flint A, Wahl RL. Glucose transporters and FDG uptake in untreated primary human non-small cell lung cancer. J Nucl Med. 1999 Apr;40(4):556-65. PMID 10210213
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Идентификаторы
NCT: NCT06262386 · 202202172B0