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Table 2 Real-world examples, applying the CanTest Framework

From: Evaluating diagnostic strategies for early detection of cancer: the CanTest framework

Phases of the CanTest Framework POPULATION TEST COMPARATORS OUTCOMES Examples
CA125 for detecting ovarian cancer CytoSponge™ for detecting Barrett’s Oesophagus (at high risk for oesophageal adenocarcinoma) CancerSEEK biomarker panel for detecting 8 common cancer types
DEFINITIONS/background      Cancer Antigen (CA)125 is a serum biomarker for epithelial ovarian cancer. It is utilized in strategies to distinguish benign from malignant pelvic masses pre-surgery and in the triage of women in primary care. It has been evaluated as part of screening strategies but is not currently used in that setting. A non-endoscopic ‘sponge on a string’ test, used for the diagnosis of oesophageal squamous carcinomas in high-risk areas, was adapted for Barratt’s Oesophagus (BO) by combining it with immunocytology A blood test to detect 8 common cancer types through assessment of the levels of circulating proteins and mutations in cell-free DNA
Phase 1 Selection of test and initial measures of single test performance Highly selected single Reference standard Performance    
 Analytic validity      Multiple studies e.g. Bast et al. 1983a: assay developed and threshold set (> 35 U/ml); 1% of healthy patients and 82% of patients with ovarian carcinomas have levels > 35 U/ml.
Mongia et al. 2006b: Comparison of 6 CA125 assays; acceptable performance and comparability.
Lao-Sirieix et al. 2009j: Trefoil factor 3 (TFF3) expressed to high levels in BO compared to normal oesophagus or gastric mucosa; sensitivity 78%, specificity 94% Cohen et al. 2018n:
For non-metastatic cancers: sensitivity 69–98% for 5 cancer types; specificity > 99%
 Diagnostic accuracy      Multiple studies e.g. Jacobs et al. 1989c: Pooled sensitivity for ovarian cancer 85%. N/A N/A
Phase 2 Measures of clinical test performance Highly selecte Single Reference performance    
 Diagnostic accuracy d     Multiple studies e.g. Maggino et al. 1994d: Sensitivity 78.3%, specificity 82% for ovarian cancer in patients with a pelvic mass. Ross-Innes et al, 2015k: Sensitivity 79.9%, specificity 92.4% for BO in patients referred with dyspepsia and reflux symptoms. N/A
 Internal validity / reproducibility Multiple studies e.g. Medeiros et al. 2009e: systematic review, Area Under the Curve of 0.9 for distinguishing malignant/borderline and benign tumours. N/A N/A
Phase 3 Impact on clinical decision-making & health outcomes Selected/Real-world Single/combinations Reference/ usual care Medical decision making    
 Diagnostic accuracy      N/A Kadri et al, 2010l. Accuracy for BO in primary care: sensitivity 90% & specificity 93.5% for clinically relevant segments of 2 cm or more compared with gastroscopy. N/A
 Effects on patients N/A Kadri et al, 2010l. Acceptable for patients, and no adverse events. N/A
 Effects on clinicians Moss et al. 2013f: Explored GP views on CA125 use in Primary care.   N/A
 Effects on diagnostic triage /
 Incorporation into diagnostic strategies
     Gilbert et al. 2012g: Pilot study of symptom triggered ‘screening’ strategy incorporating CA125 and ultrasound. Study arm patients had more frequently resectable tumours than the control arm (usual care). Definitive results awaited. N/A N/A
Phase 4 Effectiveness of new diagnostic strategy on clinical outcomes Real-world Single/combinations Usual care MDM/harms    
 Effectiveness & cost-effectiveness      NICE 2011h: cost effectiveness comparison of different triaging strategies incorporating CA125. Offman et al, 2018m: BEST3 randomised trial underway comparing the Cytosponge-TFF3 test with usual care to facilitate diagnosis of oesophageal pre-cancer in primary care patients with chronic acid reflux. N/A
 Patient safety & quality      Goff et al. 2012i: Small study; symptom based testing in primary care resulted in minimal additional unnecessary procedures. N/A N/A
 Over-diagnosis      N/A N/A N/A
Phase 5 Implementation & effects at healthcare & population level Real-world    Pop health & costs    
 Effects on health system      N/A N/A N/A
 Effects on population      N/A N/A N/A
  1. a Bast et al. 1983: https://www.nejm.org/doi/full/10.1056/NEJM198310133091503?url_ver=Z39.882003&rfr_id=ori%3Arid%3Acrossref.org&rfr
  2. b Mongia et al. 2006: https://www.ncbi.nlm.nih.gov/pubmed/16690492
  3. c Jacobs et al. 1989: https://academic.oup.com/humrep/article/4/1/1/608701
  4. d Maggino et al. 1994: https://www.sciencedirect.com/science/article/pii/S0090825884711796
  5. e Medeiros et al. 2009: https://www.ncbi.nlm.nih.gov/pubmed/18995946
  6. f Moss et al. 2013: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3644283/
  7. g Gilbert et al. 2012: https://www.thelancet.com/journals/lanonc/article/PIIS1470-2045(11)70333-3/fulltext
  8. h NICE. Ovarian Cancer: The recognition and initial management of ovarian cancer. Cardiff, UK: National Collaborating Centre for Cancer, 2011
  9. I Goff et al. 2012: https://www.sciencedirect.com/science/article/pii/S0090825811008742
  10. J Lao-Sirieix et al. 2009: doi: https://doi.org/10.1136/gut.2009.180281
  11. K Ross-Innes et al. 2015: doi: https://doi.org/10.1371/journal.pmed.1001780
  12. L Kadri et al. 2010: doi: https://doi.org/10.1136/bmj.c4372
  13. M Offman et al. 2018: doi: https://doi.org/10.1186/s12885-018-4664-3
  14. N Cohen et al.2018: https://www.ncbi.nlm.nih.gov/pubmed/29348365