[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100524165":3},{"organization":4,"outcomesModule":7,"designInfo":30,"detailedDescription":34,"studyPopulation":35,"armGroups":31,"interventions":31,"overallOfficials":36,"centralContacts":40,"locations":49,"responsibleParty":115,"collaborators":118,"id":133,"slug":31,"hasResults":134,"nctId":135,"briefTitle":136,"officialTitle":137,"acronym":138,"eligibilityCriteria":139,"healthyVolunteers":134,"sex":140,"minAge":141,"maxAge":31,"enrollmentInfo":142,"targetDuration":145,"studyType":146,"phases":31,"briefSummary":147,"conditions":148,"keywords":150,"overallStatus":80,"whyStopped":31,"lastUpdateSubmitDate":157,"lastUpdatePostDateStruct":158,"startDateStruct":161,"completionDateStruct":163,"leadSponsor":165,"locationsCount":166},{"fullName":5,"class":6},"Catharina Ziekenhuis Eindhoven","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":19,"otherOutcomes":26},[9,13,16],{"measure":10,"description":11,"timeFrame":12},"Up-front ctDNA analysis is implemented into routine clinical care in the participating OncoZoN hospitals","After the Lungmarker2 study has proven up-front ctDNA analysis to be feasible and successful for diagnosis and monitoring of lung cancer, hospitals participating in this project will adopt this as routine practice. Up-front ctDNA analysis will be adopted by the other OncoZON hospitals outside the consortium through transfer of the clinical practice during the regular tumor board meetings where shared care decisions are made for individual patients.","Up to 3 years",{"measure":14,"description":15,"timeFrame":12},"Evaluate the number of driver mutations detected by up-front ctDNA analysis compared to tumor NGS analysis","Determine and compare the number of driver mutations detected by up-front ctDNA analysis with the number of driver mutations detected by tumor NGS analysis.",{"measure":17,"description":18,"timeFrame":12},"Develop decision support algorithms for the diagnosis and monitoring of lung cancer patients","Develop decision support algorithms using information from CT scans, measured tumor markers (CA125, CA15.3, CEA, CYFRA 21.1, HE-4, NSE, proGRP, SCCA) and ctDNA analysis to identify small-cell lung cancer and non-small-cell lung cancer patients (classification, diagnosis).\n\nDevelop decision support algorithms to predict therapy response, expressed as a threshold for durable clinical benefit: the progression free survival (PFS) at 6 months (as probability %), in lung cancer patients (monitoring).\n\nDifferent metrics regarding model performances will be reported: area under the receiver operating characteristic curve (AUC), area under the precision- recall curve (AUC-PR), sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV).",[20,23],{"measure":21,"description":22,"timeFrame":12},"Develop an analytical protocol for the analysis of PD-L1 expression on circulating tumor cells (CTCs) by super-resolution microscopy","Develop an analytical protocol for the isolation of CTCs from whole blood samples (measured as the number of cells per mL) and to quantify PD-L1 expression (reported as a percentage on a scale of 0% to 100%) on the isolated CTCs using super-resolution microscopy.",{"measure":24,"description":25,"timeFrame":12},"Evaluate the number of tumor NGS analyses and time to diagnosis when up-front ctDNA analysis is introduced","Determine the time to diagnosis (in days) of lung cancer (e.g., time between first visit at lung physician and the diagnosis) when using up-front ctDNA analysis compared to tumor NGS analysis, and determine the number of tumor NGS analyses that can be replaced by up-front ctDNA analysis.",[27],{"measure":28,"description":29,"timeFrame":12},"A study database is filled with all relevant clinical and diagnostic information","For the Lungmarker2 study, all information will be entered into the study database (Research manager) by personnel of the participating hospitals (research nurse, physician or lung oncology nurse) using a digital CRF. Research manager offers eCRF possibilities and enables safe and anonymous data collection, storage and management. The data collected include patient data, detailed results of diagnostic procedures and tests including imaging procedures, treatment regime and response evaluation.",{"allocation":31,"interventionModel":31,"interventionModelDescription":31,"primaryPurpose":31,"observationalModel":32,"timePerspective":33,"maskingInfo":31},null,"COHORT","PROSPECTIVE","RATIONALE: Despite scientific evidence, use of liquid biopsy (LB) in diagnosis and monitoring of lung cancer (LC) is limited since it requires major changes in diagnostic and care pathways. Analyzing tumor markers (TMs), circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) in blood (LB) can inform about the nature of the tumor, the most appropriate therapy, therapy response and resistance.\n\nOBJECTIVE: To implement up-front ctDNA analysis ('plasma first approach') into routine diagnostic work-up of all advanced stage LC patients in the Southeast of the Netherlands (the participating hospitals in the OncoZON region) and to thereby validate that significantly more information about the molecular make-up of the tumor becomes available by introduction of up-front ctDNA. To establish that the number of tissue NGS analyses decreases and time to therapeutic decision making is shortened. To build and to validate, using ctDNA, TM and other information, multiparametric decision support models that may support diagnosis, predict the outcome of the next imaging procedure and survival during follow up. The final goal is to develop a super-resolution microscopy test that can detect PD-L1 expression on CTCs.\n\nSTUDY DESIGN: Multicenter, prospective, implementation and diagnostic cohort study.\n\nSTUDY POPULATION: 800 patients suspected of having lung cancer.\n\nMAIN STUDY PARAMETERS\u002FENDPOINTS: ctDNA analysis, as additional source of genetic information, has been integrated into the diagnostic workup of LC patients and the medical benefits thereof are quantified, e.g. a significant higher percentage of patients with a driver mutation is identified by introduction of the plasma first approach. Multiparametric decision support algorithms based on imaging, TM and ctDNA analyses that identify small-cell LC (SCLC) and non-small-cell LC (NSCLC) have been developed and validated. Multiparametric decision support models have been developed that enable patient-specific timing of imaging procedures and predict survival during follow-up of LC patients. A super-resolution microscopy test for PD-L1 is developed and correlation with tumor tissue PD-L1 expression has been established.\n\nNATURE AND EXTENT OF THE BURDEN AND RISKS ASSOCIATED WITH PARTICIPATION, BENEFIT AND GROUP RELATEDNESS: At diagnosis, an extra 10 mL of blood are drawn during a routine venipuncture. Patients with advanced stage LC (stage IIIb\u002Fc or IV) undergo an extra venipuncture (40 mL).The longest follow up period for a patient is 36 months with a maximum of 20 blood draws. The volume per draw ranges from 10-40 mL. The risks of a venipuncture are negligible and the burden minimal. Those patients for whom a targetable mutation is found by ctDNA analysis benefit from the advantages of targeted therapy, i.e. better survival and less side effects of the treatment.","800 individuals, \\>18 years of age, suspected of lung cancer and referred to a lung physician in one of the participating centers are included in the study.",[37],{"name":38,"affiliation":5,"role":39},"Volkher Scharnhorst, Prof.Dr.","PRINCIPAL_INVESTIGATOR",[41,46],{"name":42,"role":43,"phone":44,"phoneExt":31,"email":45},"Hao Cao, MSc","CONTACT","+31402398644","hao.cao@catharinaziekenhuis.nl",{"name":38,"role":43,"phone":47,"phoneExt":31,"email":48},"+31402398640","volkher.scharnhorst@catharinaziekenhuis.nl",[50,67,79,91,103],{"facility":51,"status":52,"city":53,"state":54,"zip":55,"country":56,"countryCode":57,"cosmosGeoPoint":58,"geoPoint":63,"contacts":64},"Zuyderland Medical Center","NOT_YET_RECRUITING","Heerlen","Limburg","6419PC","Netherlands","NL",{"type":59,"coordinates":60},"Point",[61,62],5.98154,50.88365,{"lat":62,"lon":61},[65],{"name":66,"role":43,"phone":31,"phoneExt":31,"email":31},"Michiel Gronenschild, MD",{"facility":68,"status":52,"city":69,"state":54,"zip":70,"country":56,"countryCode":57,"cosmosGeoPoint":71,"geoPoint":75,"contacts":76},"Maastricht University Medical Center","Maastricht","6229HX",{"type":59,"coordinates":72},[73,74],5.68889,50.84833,{"lat":74,"lon":73},[77],{"name":78,"role":43,"phone":31,"phoneExt":31,"email":31},"Lizza Hendriks, MD, PhD",{"facility":5,"status":80,"city":81,"state":82,"zip":83,"country":56,"countryCode":57,"cosmosGeoPoint":84,"geoPoint":88,"contacts":89},"RECRUITING","Eindhoven","North Brabant","5623EJ",{"type":59,"coordinates":85},[86,87],5.47778,51.44083,{"lat":87,"lon":86},[90],{"name":42,"role":43,"phone":44,"phoneExt":31,"email":45},{"facility":92,"status":52,"city":93,"state":82,"zip":94,"country":56,"countryCode":57,"cosmosGeoPoint":95,"geoPoint":99,"contacts":100},"St. Anna Ziekenhuis","Geldrop","5664EH",{"type":59,"coordinates":96},[97,98],5.55972,51.42167,{"lat":98,"lon":97},[101],{"name":102,"role":43,"phone":31,"phoneExt":31,"email":31},"Gerben Stege, MD, PhD",{"facility":104,"status":52,"city":105,"state":82,"zip":106,"country":56,"countryCode":57,"cosmosGeoPoint":107,"geoPoint":111,"contacts":112},"Máxima Medisch Centrum","Veldhoven","5504DB",{"type":59,"coordinates":108},[109,110],5.40278,51.41833,{"lat":110,"lon":109},[113],{"name":114,"role":43,"phone":31,"phoneExt":31,"email":31},"Magdolen El Soud-Youssef, MD",{"type":39,"investigatorFullName":116,"investigatorTitle":117,"investigatorAffiliation":5,"oldNameTitle":31,"oldOrganization":31},"Volkher Scharnhorst","Prof. Dr. (Clinical Chemist)",[119,121,124,126,128,129,131],{"name":120,"class":6},"Eindhoven University of Technology",{"name":122,"class":123},"Roche BV Netherlands","UNKNOWN",{"name":125,"class":6},"Maxima Medical Center",{"name":127,"class":6},"Zuyderland Medisch Centrum",{"name":68,"class":6},{"name":130,"class":6},"St. Anna Ziekenhuis, Geldrop, Netherlands",{"name":132,"class":6},"The Netherlands Cancer Institute","100524165",false,"NCT06105177","Implementation of Up-front ctDNA Into Lung Cancer Care and Development of Liquid Biopsy-based Decision Support Models - LM² Study","Implementation of Up-front ctDNA Analysis Into Lung Cancer Care and Development of Liquid Biopsy-based Decision Support Models - the Lungmarker² Study","LM2","Inclusion Criteria:\n\n* Aged 18 or above and suspected of having lung cancer\n\nExclusion Criteria:\n\n* Presence of another malignant tumor, i.e. diagnosed with a tumor in the past 5 years","ALL","18 Years",{"count":143,"type":144},800,"ESTIMATED","36 Months","OBSERVATIONAL","Despite scientific evidence, use of liquid biopsy (LB) in diagnosis and monitoring of lung cancer (LC) is limited since it requires major changes in diagnostic and care pathways. Analyzing tumor markers (TMs), circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) in blood (LB) can inform about the nature of the tumor, the most appropriate therapy, therapy response and resistance.\n\nLungmarker2 is a multicenter, prospective, implementation and diagnostic cohort study. This study aims to implement up-front ctDNA analysis ('plasma first approach') into routine diagnostic work-up of all advanced stage LC patients in the Southeast of the Netherlands (the participating hospitals in the OncoZON region). Thereby, additional information about the molecular make-up of the tumor becomes available, the number of tissue Next-Generation Sequencing (NGS) analyses will decrease and time to therapeutic decision making is shortened. Next, using ctDNA, TM and other information, multi-parametric decision support models are built and validated that may support diagnosis, predict the outcome of the next imaging procedure and progression-free survival during follow-up. The final goal is to develop a super-resolution microscopy test that can detect PD-L1 expression on CTCs.",[149],"Lung Cancer",[151,152,153,154,155,156],"lungmarker2 study","lung cancer","liquid biopsy","ctDNA","CTCs","tumormarkers","2024-09-10",{"date":159,"type":160},"2024-09-19","ACTUAL",{"date":162,"type":160},"2023-10-31",{"date":164,"type":144},"2026-10",{"name":5,"class":6},5]