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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