RDC Biomarker Study

NCT05876676 | Recruiting

• 3 other identifiers: 555753826306766
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 10

Brief Summary

Rapid Diagnostic Centres Rapid Diagnostic Centres (RDC) were built to diagnose patients who have common symptoms that occur in cancer, but it is unclear if they have cancer or not. These symptoms include:

• Weight loss
• Fatigue
• Cough
• GP suspicion Only 1 in every 10 patients (10%) referred to an RDC will have cancer. Some of the patients with cancer may have been more likely to develop cancer due to inherited or environmental factors. Some of the patients who don't have cancer may also be at higher risk of developing cancer at another time due to inherited or environmental factors. Aims The goal of this observational study is to develop a new blood or non-blood test that could help doctors at RDC:
• detect which patients have cancer through a simple and quick blood or non-blood test
• detect patients who are at higher risk of having cancer. This is so they can be monitored or guided towards cancer-screening programmes Main End Points
• The study will be considered a success if a test or mixture of tests is developed that can correctly sort patients into cancer or non-cancer groups.
• Also, the study will be considered a success if a test or mixture of tests can show what type of cancer a patient has if they have cancer. Tests To create this new blood or non-blood test the study will take the following samples from 1000 patients in the RDC Biomarker Study:
• Breath samples (around 300 patients) - People with cancer have different levels of chemicals in their breath than people without cancer. The study hopes to develop a breath test which could show if a patient has cancer or not.
• Blood samples ( around 1000 patients) - The study hopes to develop a blood test that could show if a patient has cancer or not
• Saliva samples (around 1000 patients) - For many cancers, while there is a genetic component there is no one single gene that causes cancer. Instead, it can be a combination of hundreds of genes that causes the risk of cancer in a person to go up. The study hopes to develop a test which could provide a risk score. This risk score is called a 'polygenic risk score' which would tell doctors how likely a patient is to get cancer. Method Patients who meet the criteria to be able to join the study will be asked either via telephone before their appointment, or face-to-face at an appointment at the RDC if they would like to join the study. If they agree to join the study they will read a patient information sheet and sign a consent form to say they understand what the study requires. The patient will then provide blood and saliva samples and in some cases breath samples at their first appointment. They will be then asked to provide further samples (up to three) at their follow-up appointments. Please see below for samples that will be asked for at each appointment: First appointment: Breath (not all sites), Blood, Saliva (not all sites), Survey Follow-up 1: Any samples that could not be taken at the first appointment Follow-up 2: Any samples that could not be taken at the first appointment The patient will be provided with a Study ID to identify their samples. This is a unique code to identify each person on the study. Only the site that recruited the participant will have access to the personal information that matches which patients is known by which Study ID. All organisations external to the site will only know the patient as the Study ID. An example of the study ID could be RDCRMH001. A trained clinical member of the research team at the RDC will take the sample and ship it to the relevant laboratory for testing. As well as blood and non-blood tests, information about the patients will be collected This includes routinely collected clinical data alongside investigation results. No patient identifiable information such as:
• Name
• Address
• Date of birth
• Contact details will be collected, and a Study ID will be used to identify the data. A patient questionnaire will be sent out to patients to complete for each appointment asking questions about the patient's health. The RDC doctors treating the patient will see survey answers before the appointment to allow them to act about anything worrying. For a small group of patients anonymised copies of thier scans from their medical records will also be taken. Study Duration Once the study has recruited 1000 patients, it will close to recruitment. These patients will then be followed up for 12 months following the date they joined the study.

Conditions

Cancer

Outcome Measures

Primary Outcomes (4)

• Accuracy of Clinical Data Analysis

  The main analysis, including clinical data values, will be descriptive and will be focused to inform future prospective studies. For continuous variables, the mean and standard deviation will be presented, together with the mean between-group difference, and 95% confidence interval. For binary outcomes, the percentage and frequency of patients in the outcome category of interest will be presented. When necessary intracluster correlation coefficients will be reported, together with 95% confidence interval. Where appropriate p-values will be presented.

  5 years

• Accuracy of Polygenic Risk Scores

  For most laboratory data analysis, the known relevance of a positive detection through a clinical biomarker shall not be known prior to the completion of data analysis, however for PRS analysis this would theoretically be able to provide information on 10-year and lifetime cancer risk for breast, colon, endometrial, melanoma, ovarian, pancreas, and prostate cancers. The level of risk will be determined as a risk-ratio of 2 or ≥3 compared to the general population for moderate- and high-risk individuals respectively.

  5 years

• Number of patients with accurate Imaging Radiomics and Composite Analysis

  Inclusion of radiomics data will be assessed for subsets of patients where robust imaging data and appropriate techniques for analysis exist, noting the predominance evidence available for certain tumour types such as lung cancer.

  5 years

• Number of Participants with Multiparametric and ML Analyse outcome measures

  The study will explore the role of multi-parametric predictors by optimising convolutional neural networks (CNN) or other deep learning tool to classify patients into outcome classes.

  5 years

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients across England and Wales with non specific cancer symptoms that are referred to Rapid Diagnosis Centres (England) or Rapid Diagnostic Clinics (Wales) participating in the RDC Biomarker Study.

You may qualify if:

• Patients referred to undergo investigation for suspected cancer within a non-tumour site specific RDC
• Age \> 18 years

You may not qualify if:

• Previously treated (treatment completed within 5 years preceding recruitment)
• Current confirmed diagnosis of active malignancy
• Unable to or unwilling to give informed consent

Sponsors & Collaborators

• Royal Marsden NHS Foundation Trust: lead

Study Sites (10)

Aneurin Bevan University Local Health Board

Abergavenny, United Kingdom

RECRUITING

Glan Clwyd

Bodelwyddan, United Kingdom

RECRUITING

Harrogate and District NHS Foundation Trust

Harrogate, United Kingdom

RECRUITING

Kingston and Richmond NHS Foundation Trust

Kingston, United Kingdom

RECRUITING

Ysbyty Gwynedd

Llandudno, United Kingdom

RECRUITING

Chelsea and Westminster Hospital NHS Foundation Trust - Chelsea and Westminster

London, United Kingdom

RECRUITING

Chelsea and Westminster Hospital NHS Foundation Trust - West Middlesex

London, United Kingdom

RECRUITING

North Middlesex University Hospital NHS Trust

London, United Kingdom

RECRUITING

South Tees Hospitals NHS Foundation Trust

Middlesbrough, United Kingdom

RECRUITING

Northern Care Alliance NHS Foundation Trust

Salford, United Kingdom

RECRUITING

Related Publications (18)

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  PMID: 32624574 BACKGROUND

• Dolly SO, Jones G, Allchorne P, Wheeler D, Ali S, Mukadam Y, Zheng S, Rahman L, Sindhar J, Moss CL, Harari D, Van Hemelrijck M, Cunliffe A, De Michele LV. The effectiveness of the Guy's Rapid Diagnostic Clinic (RDC) in detecting cancer and serious conditions in vague symptom patients. Br J Cancer. 2021 Mar;124(6):1079-1087. doi: 10.1038/s41416-020-01207-7. Epub 2021 Jan 5.

  PMID: 33402736 BACKGROUND

• Vasilakis C, Forte P. Setting up a rapid diagnostic clinic for patients with vague symptoms of cancer: a mixed method process evaluation study. BMC Health Serv Res. 2021 Apr 17;21(1):357. doi: 10.1186/s12913-021-06360-0.

  PMID: 33865373 BACKGROUND

• Murchison AG, Moreland JA, Gleeson F. Incidental findings in a referral pathway for non-specific cancer symptoms. Clin Imaging. 2021 Sep;77:9-12. doi: 10.1016/j.clinimag.2021.01.042. Epub 2021 Feb 17.

  PMID: 33610971 BACKGROUND

• Sewell B, Jones M, Gray H, Wilkes H, Lloyd-Bennett C, Beddow K, Bevan M, Fitzsimmons D. Rapid cancer diagnosis for patients with vague symptoms: a cost-effectiveness study. Br J Gen Pract. 2020 Feb 27;70(692):e186-e192. doi: 10.3399/bjgp20X708077. Print 2020 Mar.

  PMID: 31932296 BACKGROUND

• Ardila D, Kiraly AP, Bharadwaj S, Choi B, Reicher JJ, Peng L, Tse D, Etemadi M, Ye W, Corrado G, Naidich DP, Shetty S. End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography. Nat Med. 2019 Jun;25(6):954-961. doi: 10.1038/s41591-019-0447-x. Epub 2019 May 20.

  PMID: 31110349 BACKGROUND

• McPhail S, Johnson S, Greenberg D, Peake M, Rous B. Stage at diagnosis and early mortality from cancer in England. Br J Cancer. 2015 Mar 31;112 Suppl 1(Suppl 1):S108-15. doi: 10.1038/bjc.2015.49.

  PMID: 25734389 BACKGROUND

• Neal RD, Tharmanathan P, France B, Din NU, Cotton S, Fallon-Ferguson J, Hamilton W, Hendry A, Hendry M, Lewis R, Macleod U, Mitchell ED, Pickett M, Rai T, Shaw K, Stuart N, Torring ML, Wilkinson C, Williams B, Williams N, Emery J. Is increased time to diagnosis and treatment in symptomatic cancer associated with poorer outcomes? Systematic review. Br J Cancer. 2015 Mar 31;112 Suppl 1(Suppl 1):S92-107. doi: 10.1038/bjc.2015.48.

  PMID: 25734382 BACKGROUND

• Nicholson BD, Hamilton W, Koshiaris C, Oke JL, Hobbs FDR, Aveyard P. The association between unexpected weight loss and cancer diagnosis in primary care: a matched cohort analysis of 65,000 presentations. Br J Cancer. 2020 Jun;122(12):1848-1856. doi: 10.1038/s41416-020-0829-3. Epub 2020 Apr 15.

  PMID: 32291391 BACKGROUND

• Zhou B, Xu K, Zheng X, Chen T, Wang J, Song Y, Shao Y, Zheng S. Application of exosomes as liquid biopsy in clinical diagnosis. Signal Transduct Target Ther. 2020 Aug 3;5(1):144. doi: 10.1038/s41392-020-00258-9.

  PMID: 32747657 BACKGROUND

• Hanna GB, Boshier PR, Markar SR, Romano A. Accuracy and Methodologic Challenges of Volatile Organic Compound-Based Exhaled Breath Tests for Cancer Diagnosis: A Systematic Review and Meta-analysis. JAMA Oncol. 2019 Jan 1;5(1):e182815. doi: 10.1001/jamaoncol.2018.2815. Epub 2019 Jan 10.

  PMID: 30128487 BACKGROUND

• Liu MC, Oxnard GR, Klein EA, Swanton C, Seiden MV; CCGA Consortium. Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA. Ann Oncol. 2020 Jun;31(6):745-759. doi: 10.1016/j.annonc.2020.02.011. Epub 2020 Mar 30.

  PMID: 33506766 BACKGROUND

• Sud A, Turnbull C, Houlston R. Will polygenic risk scores for cancer ever be clinically useful? NPJ Precis Oncol. 2021 May 21;5(1):40. doi: 10.1038/s41698-021-00176-1. No abstract available.

  PMID: 34021222 BACKGROUND

• Al-Mekhlafi A, Becker T, Klawonn F. Sample size and performance estimation for biomarker combinations based on pilot studies with small sample sizes. Communications in Statistics-Theory and Methods. 2020; 1-15

  BACKGROUND

• Pepe MS, Li CI, Feng Z. Improving the quality of biomarker discovery research: the right samples and enough of them. Cancer Epidemiol Biomarkers Prev. 2015 Jun;24(6):944-50. doi: 10.1158/1055-9965.EPI-14-1227. Epub 2015 Apr 2.

  PMID: 25837819 BACKGROUND

• Cruz Rivera S, Liu X, Chan AW, Denniston AK, Calvert MJ; SPIRIT-AI and CONSORT-AI Working Group. Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension. Lancet Digit Health. 2020 Oct;2(10):e549-e560. doi: 10.1016/S2589-7500(20)30219-3. Epub 2020 Sep 9.

  PMID: 33328049 BACKGROUND

Biospecimen

Retention: SAMPLES WITH DNA

Saliva - polygenic risk score - all patients/all sites Bloods - methylation - all patients/all sites Bloods - Exosome - 300 patients/London sites only Bloods - Immunophenotype - 300 patients/London sites only Breath Condensate - Breathanomics - 300 patients/5 London sites

MeSH Terms

Conditions

Neoplasms

Study Officials

• Richard Lee, Dr

  Royal Marsden NHS Foundation Trust

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Serwaa Lashley

CONTACT

020 7808 2603; rdcbio@rmh.nhs.uk

Richard Lee

CONTACT

020 7808 2603; richard.lee@rmh.nhs.uk

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: CROSS SECTIONAL
• Target Duration: 12 Months
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 17, 2023
• First Posted: May 25, 2023
• Study Start: July 10, 2023
• Primary Completion (Estimated): July 10, 2027
• Study Completion (Estimated): July 10, 2032
• Last Updated: April 17, 2025

Record last verified: 2025-04

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL
• Time Frame: 5 years \[TBC depending on access requests\]
• Access Criteria: Agreement by Trial Management Group with representation from PI for each site from which data originated. Data Sharing Agreement between provider and partner.

Locations

GB (10)