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Lung cancer is the most common cancer type worldwide, with more than 1.1 million annual deaths. There are two types of the disease, namely non-small cell lung cancer (NSCLC) and small-cell lung cancer (SCLC), with the first accounting for 85% of the total number of cases. The 5-year survival across stages remains disappointingly low, around 10% in most countries, due to a high incidence of both loco-regional and distant failure [3]. However, during the last decade improved radiotherapy techniques allowed an increase of the radiation dose, while at the same time more effective chemo radiation schemes are being applied. These developments have lead to improved outcome in terms of survival. As the TNM staging system is highly inaccurate for the prediction of survival outcome for non-surgical patients, attempts have been made to develop a more accurate risk stratification for these patients [1,2]. A model based on clinical variables yielded an AUC of 0.74, which was encouraging, but also left room for improvement [2]. An extended model, which included clinical as well as biomarker variables, reached a higher AUC, but the limited number of patients included in this study made it impossible to draw definitive conclusions [1].
New prognostic parameters can be retrieved from several sources, which include anatomic, molecular and functional imaging, genomics, proteomics and clinical analysis of patients. The unlimited amount of information is expected to lead to more accurate predictions of individual treatment outcome [4].
The analysis of biomarkers, including proteins, is a fast developing, promising and challenging area of research. Biomarkers can measure or evaluate normal biological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention. Oncoproteins are produced by, or in response to tumor cells, and may be secreted in the circulation of patients. As tissue sampling is often not possible in lung cancer patients, blood sample collection by venepuncture offers an attractive alternative, which is safe and easy to implement. A number of studies described the prognostic and predictive value of blood biomarkers for NSCLC [5-7]. In this study we will investigate the prognostic value of blood biomarkers related to 1) hypoxia: Osteopontin (OPN), carbonic anhydrase IX (CA-9), and lactate dehydrogenase (LDH); 2) inflammation - interleukin 6 (IL-6), IL-8, and C-reactive protein (CRP), and α-2-macroglobulin (α-2M); and 3) tumor load: Carcinoembryonic antigen (CEA) and cytokeratin fragment (CYFRA 21-1).
Lung cancer is the most common cancer type worldwide, with more than 1.1 million annual deaths. There are two types of the disease, namely non-small cell lung cancer (NSCLC) and small-cell lung cancer (SCLC), with the first accounting for 85% of the total number of cases. The 5-year survival across stages remains disappointingly low, around 10% in most countries, due to a high incidence of both loco-regional and distant failure [3]. However, during the last decade improved radiotherapy techniques allowed an increase of the radiation dose, while at the same time more effective chemo radiation schemes are being applied. These developments have lead to improved outcome in terms of survival. As the TNM staging system is highly inaccurate for the prediction of survival outcome for non-surgical patients, attempts have been made to develop a more accurate risk stratification for these patients [1,2]. A model based on clinical variables yielded an AUC of 0.74, which was encouraging, but also left room for improvement [2]. An extended model, which included clinical as well as biomarker variables, reached a higher AUC, but the limited number of patients included in this study made it impossible to draw definitive conclusions [1].
New prognostic parameters can be retrieved from several sources, which include anatomic, molecular and functional imaging, genomics, proteomics and clinical analysis of patients. The unlimited amount of information is expected to lead to more accurate predictions of individual treatment outcome [4].
The analysis of biomarkers, including proteins, is a fast developing, promising and challenging area of research. Biomarkers can measure or evaluate normal biological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention. Oncoproteins are produced by, or in response to tumor cells, and may be secreted in the circulation of patients. As tissue sampling is often not possible in lung cancer patients, blood sample collection by venepuncture offers an attractive alternative, which is safe and easy to implement. A number of studies described the prognostic and predictive value of blood biomarkers for NSCLC [5-7]. In this study we will investigate the prognostic value of blood biomarkers related to 1) hypoxia: Osteopontin (OPN), carbonic anhydrase IX (CA-9), and lactate dehydrogenase (LDH); 2) inflammation - interleukin 6 (IL-6), IL-8, and C-reactive protein (CRP), and α-2-macroglobulin (α-2M); and 3) tumor load: Carcinoembryonic antigen (CEA) and cytokeratin fragment (CYFRA 21-1).
The investigators hypothesize that:
Measurement procedure: Blood samples, that were collected, processed and stored in the Maastro biobank in a standardized way, will be used to measure CRP, LDH, Osteopontin, CA-9 IL-6, IL-8, CEA, CYFRA 21-1, and α-2M. Clinical data will be retrieved from the electronic medical files.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| NSCLC | The cohort consists of approximately 250 patients. As a rule of thumb 5-10 events per variable are needed to avoid overfitting a model. To model 6 clinical variables + 9 biomarker variables 75-150 events are needed. Assuming a two-year survival of 40%, the calculated (constant) hazard rate is 0.46 per year. With an inclusion rate of 50 patients per year, and a follow-up time varying between 0.5 and 4 year, at the time of analysis (November/December 2013) it is expected that there will be 138 events available for analysis. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Blood samples | Other | Blood samples, that were collected, processed and stored in the Maastro biobank in a standardized way, will be used to measure CRP, LDH, Osteopontin, CA-9 IL-6, IL-8, CEA, CYFRA 21-1, and α-2M. Clinical data will be retrieved from the electronic medical files. |
| Measure | Description | Time Frame |
|---|---|---|
| Correlation of blood biomarkers to overall survival | 4 years |
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The cohort consists of approximately 250 patients. As a rule of thumb 5-10 events per variable are needed to avoid overfitting a model. To model 6 clinical variables + 9 biomarker variables 75-150 events are needed. Assuming a two-year survival of 40%, the calculated (constant) hazard rate is 0.46 per year. With an inclusion rate of 50 patients per year, and a follow-up time varying between 0.5 and 4 year, at the time of analysis (November/December 2013) it is expected that there will be 138 events available for analysis.
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Non-small cell lung cancer patients
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| Name | Affiliation | Role |
|---|---|---|
| Cary Oberije, PhD | Maastro Clinic, The Netherlands | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| MAASTRO clinic | Maastricht | Limburg | 6229 ET | Netherlands |
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| ID | Term |
|---|---|
| D002289 | Carcinoma, Non-Small-Cell Lung |
| ID | Term |
|---|---|
| D002283 | Carcinoma, Bronchogenic |
| D001984 | Bronchial Neoplasms |
| D008175 | Lung Neoplasms |
| D012142 | Respiratory Tract Neoplasms |
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| ID | Term |
|---|---|
| D001800 | Blood Specimen Collection |
| ID | Term |
|---|---|
| D013048 | Specimen Handling |
| D019411 | Clinical Laboratory Techniques |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
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|
| D013899 |
| Thoracic Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
| D011677 | Punctures |
| D013514 | Surgical Procedures, Operative |
| D008919 | Investigative Techniques |