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Usefulness of Blood Biomarkers for Overall Survival in NSCLC

10. april 2014 oppdatert av: Maastricht Radiation Oncology

Use of Blood Biomarkers to Predict Overall Survival for Non-Small-cell Lung Cancer (NSCLC) Patients Treated With (Chemo)Radiotherapy.

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).

  1. Dehing-Oberije C, Aerts H, Yu S, De Ruysscher D, Menheere P, Hilvo M, et al. Development and validation of a prognostic model using blood biomarker information for prediction of survival of non-small-cell lung cancer patients treated with combined chemotherapy and radiation or radiotherapy alone (NCT00181519, NCT00573040, and NCT00572325). Int J Radiat Oncol Biol Phys. 2011 Oct 1;81(2):360-368.
  2. Dehing-Oberije C, Yu S, De Ruysscher D, Meersschout S, Van Beek K, Lievens Y, et al. Development and external validation of prognostic model for 2-year survival of non-small-cell lung cancer patients treated with chemoradiotherapy. Int J Radiat Oncol Biol Phys. 2009 Jun 1;74(2):355-362.
  3. Travis WD, Brambilla E, Müller-Hermelink HK, Harris CC. World Health Organization Classification of Tumours: Pathology and Genetics of Tumours of the Lung, Pleura, Thymus and Heart. Paul Kleihues MD, Leslie H. Sobin MD, editors. Lyon, France: IARC Press, International Agency for Research on Cancer; 2004.
  4. Lambin P, Rios-Velazquez E, Leijenaar R, Carvalho S, van Stiphout RG, Granton P, et al. Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer. 2012 Mar;48(4):441-446.
  5. Donati V, Boldrini L, Dell'Omodarme M, Prati MC, Faviana P, Camacci T, et al. Osteopontin expression and prognostic significance in non-small cell lung cancer. Clin Cancer Res. 2005 Sep 15;11(18):6459-6465.
  6. Muley T, Fetz TH, Dienemann H, Hoffmann H, Herth FJ, Meister M, et al. Tumor volume and tumor marker index based on CYFRA 21-1 and CEA are strong prognostic factors in operated early stage NSCLC. Lung Cancer. 2008 Jun;60(3):408-415.
  7. Pine SR, Mechanic LE, Enewold L, Chaturvedi AK, Katki HA, Zheng YL, et al. Increased levels of circulating interleukin 6, interleukin 8, C-reactive protein, and risk of lung cancer. J Natl Cancer Inst. 2011 Jul 20;103(14):1112-1122.

Studieoversikt

Status

Fullført

Intervensjon / Behandling

Detaljert beskrivelse

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).

  1. Dehing-Oberije C, Aerts H, Yu S, De Ruysscher D, Menheere P, Hilvo M, et al. Development and validation of a prognostic model using blood biomarker information for prediction of survival of non-small-cell lung cancer patients treated with combined chemotherapy and radiation or radiotherapy alone (NCT00181519, NCT00573040, and NCT00572325). Int J Radiat Oncol Biol Phys. 2011 Oct 1;81(2):360-368.
  2. Dehing-Oberije C, Yu S, De Ruysscher D, Meersschout S, Van Beek K, Lievens Y, et al. Development and external validation of prognostic model for 2-year survival of non-small-cell lung cancer patients treated with chemoradiotherapy. Int J Radiat Oncol Biol Phys. 2009 Jun 1;74(2):355-362.
  3. Travis WD, Brambilla E, Müller-Hermelink HK, Harris CC. World Health Organization Classification of Tumours: Pathology and Genetics of Tumours of the Lung, Pleura, Thymus and Heart. Paul Kleihues MD, Leslie H. Sobin MD, editors. Lyon, France: IARC Press, International Agency for Research on Cancer; 2004.
  4. Lambin P, Rios-Velazquez E, Leijenaar R, Carvalho S, van Stiphout RG, Granton P, et al. Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer. 2012 Mar;48(4):441-446.
  5. Donati V, Boldrini L, Dell'Omodarme M, Prati MC, Faviana P, Camacci T, et al. Osteopontin expression and prognostic significance in non-small cell lung cancer. Clin Cancer Res. 2005 Sep 15;11(18):6459-6465.
  6. Muley T, Fetz TH, Dienemann H, Hoffmann H, Herth FJ, Meister M, et al. Tumor volume and tumor marker index based on CYFRA 21-1 and CEA are strong prognostic factors in operated early stage NSCLC. Lung Cancer. 2008 Jun;60(3):408-415.
  7. Pine SR, Mechanic LE, Enewold L, Chaturvedi AK, Katki HA, Zheng YL, et al. Increased levels of circulating interleukin 6, interleukin 8, C-reactive protein, and risk of lung cancer. J Natl Cancer Inst. 2011 Jul 20;103(14):1112-1122.

The investigators hypothesize that:

  • Higher levels of blood biomarkers are associated with worse survival
  • The biomarker information will improve the performance of prediction models, that were previously developed and validated [1, 2]
  • Subgroups of patients can be identified that benefit most in terms of a more accurate prediction of survival when using biomarker information

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.

Studietype

Observasjonsmessig

Registrering (Faktiske)

250

Kontakter og plasseringer

Denne delen inneholder kontaktinformasjon for de som utfører studien, og informasjon om hvor denne studien blir utført.

Studiesteder

    • Limburg
      • Maastricht, Limburg, Nederland, 6229 ET
        • Maastro clinic

Deltakelseskriterier

Forskere ser etter personer som passer til en bestemt beskrivelse, kalt kvalifikasjonskriterier. Noen eksempler på disse kriteriene er en persons generelle helsetilstand eller tidligere behandlinger.

Kvalifikasjonskriterier

Alder som er kvalifisert for studier

  • Barn
  • Voksen
  • Eldre voksen

Tar imot friske frivillige

Nei

Kjønn som er kvalifisert for studier

Alle

Prøvetakingsmetode

Ikke-sannsynlighetsprøve

Studiepopulasjon

Non-small cell lung cancer patients

Beskrivelse

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.

Studieplan

Denne delen gir detaljer om studieplanen, inkludert hvordan studien er utformet og hva studien måler.

Hvordan er studiet utformet?

Designdetaljer

  • Observasjonsmodeller: Kohort
  • Tidsperspektiver: Potensielle

Kohorter og intervensjoner

Gruppe / Kohort
Intervensjon / Behandling
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.
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.

Hva måler studien?

Primære resultatmål

Resultatmål
Tidsramme
Correlation of blood biomarkers to overall survival
Tidsramme: 4 years
4 years

Samarbeidspartnere og etterforskere

Det er her du vil finne personer og organisasjoner som er involvert i denne studien.

Etterforskere

  • Hovedetterforsker: Cary Oberije, PhD, Maastro Clinic, The Netherlands

Studierekorddatoer

Disse datoene sporer fremdriften for innsending av studieposter og sammendragsresultater til ClinicalTrials.gov. Studieposter og rapporterte resultater gjennomgås av National Library of Medicine (NLM) for å sikre at de oppfyller spesifikke kvalitetskontrollstandarder før de legges ut på det offentlige nettstedet.

Studer hoveddatoer

Studiestart

1. september 2013

Primær fullføring (Faktiske)

1. februar 2014

Studiet fullført (Faktiske)

1. mars 2014

Datoer for studieregistrering

Først innsendt

3. september 2013

Først innsendt som oppfylte QC-kriteriene

5. september 2013

Først lagt ut (Anslag)

6. september 2013

Oppdateringer av studieposter

Sist oppdatering lagt ut (Anslag)

11. april 2014

Siste oppdatering sendt inn som oppfylte QC-kriteriene

10. april 2014

Sist bekreftet

1. april 2014

Mer informasjon

Begreper knyttet til denne studien

Legemiddel- og utstyrsinformasjon, studiedokumenter

Studerer et amerikansk FDA-regulert medikamentprodukt

Nei

Studerer et amerikansk FDA-regulert enhetsprodukt

Nei

produkt produsert i og eksportert fra USA

Nei

Denne informasjonen ble hentet direkte fra nettstedet clinicaltrials.gov uten noen endringer. Hvis du har noen forespørsler om å endre, fjerne eller oppdatere studiedetaljene dine, vennligst kontakt register@clinicaltrials.gov. Så snart en endring er implementert på clinicaltrials.gov, vil denne også bli oppdatert automatisk på nettstedet vårt. .

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