Reimagining the diagnostic pathway for gastrointestinal cancer

Abstract

A crisis is looming for the diagnosis of gastrointestinal cancers, one grounded only partly in the steady increase in their overall incidence. Public demand for diagnostic tests to be undertaken early and at lower levels of risk is reflected in early diagnosis being a widely held policy objective for reasons of both clinical outcome and patient experience. In the UK, urgent referrals for suspected lower gastrointestinal cancer have increased by 78% in the past 6 years, with parallel increases in endoscopy and imaging activity. Such growth in demand is unsustainable with current models of care. If gastrointestinal cancer diagnosis is to be affordable, the roles of professionals and their interactions with each other will need to be reframed while retaining public confidence in the process. In this Perspective, we consider how the relationship between medical specialists and generalists could be redefined to make better use of the skills of each while delivering optimal clinical outcomes and a good patient experience.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: The structure of the Danish three-legged diagnostic strategy.
Figure 2: A reimagined, integrated pathway for diagnosis of gastrointestinal cancer.

References

  1. 1

    Hiom, S. C. Diagnosing cancer earlier: reviewing the evidence for improving cancer survival. Br. J. Cancer 112, S1–S5 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  2. 2

    Bourne, T. et al. The impact of complaints procedures on the welfare, health and clinical practise of 7926 doctors in the UK: a cross-sectional survey. BMJ Open 5, e006687 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  3. 3

    National Cancer Registration and Analysis Service. Personal Communication (27th April 2017).

  4. 4

    Public Health England. The 2nd Atlas of Variation in NHS Diagnostic Services in England (PHE, 2017).

  5. 5

    [No authors listed.] Public health profiles. Public Health England https://fingertips.phe.org.uk/ (2017).

  6. 6

    Brown, H. et al. Scoping the future: an evaluation of endoscopy capacity across England (Cancer Research UK, 2015).

  7. 7

    National Institute for Health and Care Excellence. Suspected cancer: recognition and referral, NICE Guideline (NG12). NICE https://www.nice.org.uk/guidance/ng12 (2015).

  8. 8

    Leddin, D. et al. The 2012 SAGE wait times program: Survey of Access to GastroEnterology in Canada. Can. J. Gastroenterol. 27, 83–89 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  9. 9

    Australian Commission on Safety and Quality in Health Care. First Australian atlas of healthcare variation. ArcGIS http://acsqhc.maps.arcgis.com/apps/MapAndAppGallery/index.html?appid=6ff3b64a805240878d7b2e41cd5800a9 (2015).

  10. 10

    The Royal College of Radiologists. Clinical Radiology UK workforce census 2015 report (The Royal College of Radiologists, 2016).

  11. 11

    Centre for Workforce Intelligence. Securing the future workforce supply: gastrointestinal endoscopy workforce review (CfWI, 2017).

  12. 12

    Vedsted, P. & Olesen, F. Are the serious problems in cancer survival partly rooted in gatekeeper principles? An ecologic study. Br. J. Gen. Pract. 61, e508–e512 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  13. 13

    Rose, P. W. et al. Explaining variation in cancer survival between 11 jurisdictions in the International Cancer Benchmarking Partnership: a primary care vignette survey. BMJ Open 5, e007212 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  14. 14

    Greenfield, G., Foley, K. & Majeed, A. Rethinking primary care's gatekeeper role BMJ 354, i4803 (2016).

    Article  PubMed  Google Scholar 

  15. 15

    Rubin, G. et al. The expanding role of primary care in cancer control. Lancet Oncol. 16, 1231–1272 (2015).

    Article  PubMed  Google Scholar 

  16. 16

    Public Health England. Be Clear on Cancer. NHS England http://www.nhs.uk/be-clear-on-cancer/ (2016).

  17. 17

    Scottish Government. Detect cancer early. Scottish Government http://www.gov.scot/Topics/Health/Services/Cancer/Detect-Cancer-Early (2015).

  18. 18

    NHS England. Be Clear on Cancer evaluation update 2014. Cancer Research UK https://www.cancerresearchuk.org/sites/default/files/evaluation_results_2014.pdf (2014).

  19. 19

    Banks, J. et al. Preferences for cancer investigation: a vignette-based study of primary-care attendees. Lancet Oncol. 15, 232–240 (2014).

    Article  PubMed  Google Scholar 

  20. 20

    Elnegaard, S. et al. Self-reported symptoms and healthcare seeking in the general population -exploring “The Symptom Iceberg”. BMC Public Health 15, 685 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  21. 21

    Thompson, W. G., Heaton, K. W., Smyth, G. T. & Smyth, C. Irritable bowel syndrome in general practice: prevalence, characteristics, and referral. Gut 46, 78 (2000).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  22. 22

    [No authors listed.] Cancer statistics for the UK. Cancer Research UK http://www.cancerresearchuk.org/health-professional/cancer-statistics (2017).

  23. 23

    Smittenaar, C. R., Petersen, K. A., Stewart, K. & Moitt, N. Cancer incidence and mortality projections in the UK until 2035. Br. J. Cancer 115, 1147–1155 (2016).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  24. 24

    Neal, R. D. et al. Is increased time to diagnosis and treatment in symptomatic cancer associated with poorer outcomes? Systematic review. Br. J. Cancer 112, S92–S107 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  25. 25

    Tørring, M. L. et al. Diagnostic interval and mortality in colorectal cancer: U-shaped association demonstrated for three different datasets. J. Clin. Epidemiol. 65, 669–678 (2012).

    Article  PubMed  Google Scholar 

  26. 26

    Tørring, M. L. et al. Evidence of advanced stage colorectal cancer with longer diagnostic intervals: a pooled analysis of seven primary care cohorts comprising 11 720 patients in five countries. Br. J. Cancer https://doi.org/10.1038/bjc.2017.236 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  27. 27

    Jensen, H., Tørring, M. L., Olesen, F., Overgaard, J. & Vedsted, P. Cancer suspicion in general practice, urgent referral and time to diagnosis: a population-based GP survey and registry study. BMC Cancer 14, 636 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  28. 28

    Knottnerus, J. A. Medical decision-making by general practitioners and specialists. Fam. Pract. 8, 305–307 (1991).

    CAS  Article  PubMed  Google Scholar 

  29. 29

    Chapman, G. B. & Sonneberg, F. A. Decision Making in Health Care: Theory, Psychology and Applications (Cambridge Univ. Press, 2000).

    Google Scholar 

  30. 30

    Elstein, A. S. & Schwartz, A. Clinical problem solving and diagnostic decision making: selective review of the cognitive literature. BMJ 324, 729–732 (2002).

    Article  PubMed  PubMed Central  Google Scholar 

  31. 31

    Eaden, J. A., Abrams, K. R. & Mayberry, J. F. The risk of colorectal cancer in ulcerative colitis: a meta-analysis. Gut 48, 526–535 (2001).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  32. 32

    Stapley, S. et al. The risk of oesophago-gastric cancer in symptomatic patients in primary care: a large case-control study using electronic records. Br. J. Cancer 108, 25–31 (2013).

    CAS  Article  PubMed  Google Scholar 

  33. 33

    Hamilton, W. The CAPER studies: five case-control studies aimed at identifying and quantifying the risk of cancer in symptomatic primary care patients. Br. J. Cancer 101, S80–S86 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  34. 34

    New Zealand Guidelines Group. Suspected cancer in primary care: guidelines for investigation, referral and reducing ethnic disparities (NZGG, 2009).

  35. 35

    van den Bruel, A., Jones, C., Yang, Y., Oke, J. & Hewitson, P. People's willingness to accept overdetection in cancer screening: population survey. BMJ 350, h980 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  36. 36

    Walter, F.,M. et al. Symptoms and patient factors associated with longer time to diagnosis for colorectal cancer: results from a prospective cohort study. Br. J. Cancer 115, 533–541 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  37. 37

    The Colorectal Cancer Referral Expert Panel. Referral of patients with suspected colorectal cancer by family physicians and other primary care providers (Cancer Care Ontario, 2017).

  38. 38

    Prades, J., Espinàs, J. A., Font, R., Argimon, J. M. & Borràs, J. M. Implementing a Cancer Fast-track Programme between primary and specialised care in Catalonia (Spain): a mixed methods study. Br. J. Cancer 105, 753–759 (2011).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  39. 39

    Nicholson, B. D. et al. International variation in adherence to referral guidelines for suspected cancer: a secondary analysis of survey data. Br. J. Gen. Pract. 66, e106–e113 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  40. 40

    Møller, H. et al. Use of the English urgent referral pathway for suspected cancer and mortality in patients with cancer: cohort study. BMJ 351, h5102 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  41. 41

    Larsen, M. B., Hansen, R. P., Hansen, D. G., Olesen, F. & Vedsted, P. Secondary care intervals before and after the introduction of urgent referral guidelines for suspected cancer in Denmark: a comparative before-after study. BMC Health Services Res. 13, 348 (2013).

    Article  Google Scholar 

  42. 42

    Seifert, B. et al. The management of common gastrointestinal disorders in general practice: a survey by the European Society for Primary Care Gastroenterology (ESPCG) in six European countries. Dig. Liver Dis. 40, 659–666 (2008).

    CAS  Article  PubMed  Google Scholar 

  43. 43

    Shawihdi, M. et al. Variation in gastroscopy rate in English general practice and outcome for oesophagogastric cancer: retrospective analysis of Hospital Episode Statistics. Gut 63, 250–261 (2014).

    Article  PubMed  Google Scholar 

  44. 44

    Rubin, G. P. et al. Impact of investigations in general practice on timeliness of referral for patients subsequently diagnosed with cancer: analysis of national primary care audit data. Br. J. Cancer 112, 676–687 (2015).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  45. 45

    NHS England. Diagnostic Imaging Dataset Statistical Release 2013. NHS England https://www.england.nhs.uk/statistics/statistical-work-areas/diagnostic-imaging-dataset/ (2013).

  46. 46

    Rubin, G., Gildea, C., Wild, S., Shelton, J. & Ablett-Spence, I. Assessing the impact of an English national initiative for early cancer diagnosis in primary care. Br. J. Cancer 112, S57–S64 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  47. 47

    Roberts, S. E. et al. Survey of digestive health across Europe: Final report. Part 1: The burden of gastrointestinal diseases and the organisation and delivery of gastroenterology services across Europe. United European Gastroenterol. J. 2, 539–543 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  48. 48

    Coleman, M. P. et al. Cancer survival in Australia, Canada, Denmark, Norway, Sweden, and the UK, 1995–2007 (the International Cancer Benchmarking Partnership): an analysis of population-based cancer registry data. Lancet 377, 127–138 (2011).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  49. 49

    Vedsted, P. & Olesen, F. A differentiated approach to referrals from general practice to support early cancer diagnosis — the Danish three-legged strategy. Br. J. Cancer 112, S65–S69 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  50. 50

    Sävblom, C. Diagnostikt Centrum. Regionalt Cancer Centrum http://www.cancercentrum.se/stockholm-gotland/vara-uppdrag/prevention-och-tidig-upptackt/diagnostiskt-centrum/ (2017).

  51. 51

    Norwegian Ministry of Health and Care Services. Together — against Cancer: National Cancer Strategy 2013–2017 (Norwegian Ministry of Health and Care Services, 2013).

  52. 52

    [No authors listed.] About ACE: the Accelerate, Coordinate, Evaluate (ACE) Programme. Cancer Research UK http://www.cancerresearchuk.org/health-professional/early-diagnosis-activities/ace-programme/about-ace#ACE_About0 (2017).

  53. 53

    Lyratzopoulos, G., Wardle, J. & Rubin, G. Rethinking diagnostic delay in cancer: how difficult is the diagnosis? BMJ 349, g7400 (2014).

    Article  PubMed  Google Scholar 

  54. 54

    Hippisley-Cox, J. & Coupland, C. Symptoms and risk factors to identify men with suspected cancer in primary care: derivation and validation of an algorithm. Br. J. Gen. Pract. 63, e1–e10 (2013).

    Article  PubMed  Google Scholar 

  55. 55

    Hippisley-Cox, J. & Coupland, C. Symptoms and risk factors to identify women with suspected cancer in primary care: derivation and validation of an algorithm. Br. J. Gen. Pract. 63, e11–e21 (2013).

    Article  PubMed  Google Scholar 

  56. 56

    Moore, H. J. et al. Evaluating a computer aid for assessing stomach symptoms (ECASS): study protocol for a randomised controlled trial. Trials 17, 184 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  57. 57

    Chiang, P., Glance, D., Walker, J., Walter, F. M. & Emery, J. D. Implementing a QCancer risk tool into general practice consultations: an exploratory study using simulated consultations with Australian general practitioners. Br. J. Cancer 112, S77–S83 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  58. 58

    [No authors listed.] Ada — personal health companion app. Ada https://ada.com/ (2017).

  59. 59

    Elias, S. G. et al. Is there an added value of faecal calprotectin and haemoglobin in the diagnostic work-up for primary care patients suspected of significant colorectal disease? A cross-sectional diagnostic study. BMC Med. 14, 141 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  60. 60

    Elias, S. G. et al. Published diagnostic models safely excluded colorectal cancer in an independent primary care validation study. J. Clin. Epidemiol. 82, 149–157.e8 (2017).

    Article  PubMed  Google Scholar 

  61. 61

    [No authors listed.] Primary Care Triage Academy. Handheld ultrasound scanning. http://www.triageacademy.com/ (2017).

  62. 62

    Boots. WebMD Symptom checker. https://www.webmd.boots.com/symptoms/default.htm (2017).

  63. 63

    [No authors listed.] GI Bodyguard mobile app. Canadian Digestive Health Foundation http://cdhf.ca/fr/restez-en-bonne-sant/gi-bodyguard-mobile-app/section/about/ (2017).

  64. 64

    My Total Health. MyGiHealth app. https://mygihealth.io/ (2017).

  65. 65

    Shah, M. S. et al. Leveraging sequence-based faecal microbial community survey data to identify a composite biomarker for colorectal cancer. Gut https://doi.org/10.1136/gutjnl-2016-313189 (2017).

    Article  PubMed  Google Scholar 

  66. 66

    Villarreal-Gómez, S. & Hernandez, G. R. G. Detection of molecular markers of cancer through the use of biosensors. Biol. Med. S2, 05 (2015).

    Article  Google Scholar 

  67. 67

    Pickhardt, P. J., Hassan, C., Halligan, S. & Marmo, R. Colorectal cancer: CT colonography and colonoscopy for detection — systematic review and meta-analysis. Radiology 259, 393–405 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  68. 68

    Spada, C. et al. Colon capsule endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Guideline. Endoscopy 44, 527–536 (2012).

    CAS  Article  PubMed  Google Scholar 

  69. 69

    Palaniki, S., Blackhouse, G. & Goeree, R. Colon capsule endoscopy for the detection of colorectal polyps: an economic analysis. Ont. Health Technol. Assess. Ser. 15, 1–43 (2015).

    Google Scholar 

  70. 70

    Hashem El, B.-Serag, Jessica Davila, A. Surveillance for hepatocellular carcinoma: in whom and how? Therap Adv. Gastroenterol. 4, 5–10 (2015).

    Google Scholar 

  71. 71

    Krilaviciute, A. et al. Detection of cancer through exhaled breath: a systematic review. Oncotarget 6, 38643–38657 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  72. 72

    Arasaradnam, R. et al. Non-invasive diagnosis of pancreatic cancer through detection of volatile organic compounds in urine. Gastroenterology https://doi.org/10.1053/j.gastro.2017.09.054 (2017).

    Article  PubMed  Google Scholar 

  73. 73

    Cohen, J. D. et al. Combined circulating tumor DNA a 74nd protein biomarker-based liquid biopsy for the earlier detection of pancreatic cancers. Proc. Natl Acad. Sci. USA 114, 10202–10207 (2017).

    CAS  Article  PubMed  Google Scholar 

  74. 74

    Lin, X. et al. A serum microRNA classifier for early detection of hepatocellular carcinoma: a multicentre, retrospective, longitudinal biomarker identification study with a nested case-control study. Lancet Oncol. 16, 804–815 (2015).

    CAS  Article  PubMed  Google Scholar 

  75. 75

    Schultz, N. A. et al. MicroRNA biomarkers in whole blood for detection of pancreatic cancer. JAMA 311, 392–404 (2014).

    CAS  Article  PubMed  Google Scholar 

  76. 76

    Han, X., Wang, J. & Sun, Y. Circulating tumor DNA as biomarkers for cancer detection. Genom. Proteom. Bioinformat. 15, 59–72 (2017).

    Article  Google Scholar 

  77. 77

    Anderson, B. W. & Ahlquist, D. A. Molecular Detection of Gastrointestinal Neoplasia: Innovations in Early Detection and Screening. Gastroenterol. Clin. North Am. 45, 529–542 (2016).

    Article  PubMed  Google Scholar 

  78. 78

    Sturgeon, C. M., Lai, L. C. & Duffy, M. J. Serum tumour markers: how to order and interpret them BMJ 339, b3527 (2009).

    CAS  Article  PubMed  Google Scholar 

  79. 79

    Huang, Z. & Liu, F. Diagnostic value of serum carbohydrate antigen 19–19 in pancreatic cancer: a meta-analysis. Tumor Biol. 35, 7459–7465 (2014).

    CAS  Article  Google Scholar 

  80. 80

    Zhang, Q. et al. New developments in the early diagnosis of pancreatic cancer. Expert Rev. Gastroenterol. Hepatol. 11, 149–156 (2017).

    CAS  Article  PubMed  Google Scholar 

  81. 81

    Goggins, M. Circulating biomarkers to identify patients with resectable pancreatic cancer. J. Natl Cancer Inst. 109, djx004 (2017).

    Article  PubMed Central  Google Scholar 

  82. 82

    Balasenthil, S. et al. A plasma biomarker panel to identify surgically resectable early-stage pancreatic cancer. J. Natl Cancer Inst. 109, djw341 (2017).

    Article  PubMed Central  Google Scholar 

  83. 83

    Hori, S. S. & Gambhir, S. S. Mathematical model identifies blood biomarker-based early cancer detection strategies and limitations. Sci. Transl Med. 3, 109ra116 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  84. 84

    Kadri, S. R. Acceptability and accuracy of a non-endoscopic screening test for Barrett's oesophagus in primary care: cohort study. BMJ 342, d543 (2011).

    Article  Google Scholar 

  85. 85

    Ross-Innes, C. et al. Evaluation of a minimally invasive cell sampling device coupled with assessment of trefoil factor 3 expression for diagnosing Barrett's esophagus: a multi-center case-control study. PLoS Med. 12, e1001780 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  86. 86

    Ross-Innes, C. S. et al. Risk stratification of Barrett's oesophagus using a non-endoscopic sampling method coupled with a biomarker panel: a cohort study. Lancet Gastroenterol. Hepatol. 2, 23–31 (2017).

    Article  PubMed  Google Scholar 

  87. 87

    Usher-Smith, J., Walter, F. M., Emery, J., Win, A. K. & Griffin, S. J. Risk prediction models for colorectal cancer: a systematic review. Cancer Prev. Res. 9, 13–26 (2015).

    Article  Google Scholar 

  88. 88

    Jenkins, M. A. et al. Quantifying the utility of single nucleotide polymorphisms to guide colorectal cancer screening. Future Oncol. 12, 503–513 (2016).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  89. 89

    Independent Cancer Taskforce. Achieving world-class cancer outcomes: a strategy for England 2015–2020 (Cancer Research UK, 2015).

  90. 90

    Chambers, D. et al. Evidence for models of diagnostic service provision in the community: literature mapping exercise and focused rapid reviews. Health Services and Delivery Research, No. 4.35 (NIHR Journals Library, Southampton, UK, 2016).

    Google Scholar 

  91. 91

    [No authors listed.] The CanTest Collaborative. CanTest http://www.cantest.org (2017).

  92. 92

    Elliss-Brookes, L. et al. Routes to diagnosis for cancer - determining the patient journey using multiple routine data sets. Br. J. Cancer 107, 1220–1226 (2012).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  93. 93

    Owlstone Medical. InTERCEPT trial. Owlstone Medical https://www.owlstonemedical.com/clinical-pipeline/intercept/ (2017).

  94. 94

    QuantuMDx. Warfarin senistivity. QuantuMDx http://quantumdx.com/applications/warfarin-dosing (2017).

  95. 95

    Imperiale, T. F. et al. Multitarget stool DNA testing for colorectal-cancer screening. N. Engl. J. Med. 370, 1987–1997 (2014).

    Article  Google Scholar 

  96. 96

    IBM. Watson for Patient Record Analytics (aka Watson EMRA). IBM Research http://researcher.watson.ibm.com/researcher/view_group.php?id=7664 (2017).

  97. 97

    [No authors listed.] Arterys. Medical Imaging Cloud AI. https://arterys.com/ (2017).

Download references

Acknowledgements

This research arises from the CanTest Collaborative (Cancer diagnostic testing in primary care: a paradigm shift for cancer diagnosis), which is funded by Cancer Research UK (award number C8640/23385). G.R., F.W. and J.E. are members of the CanTest Collaborative; N.de.W. is a member of the CanTest external stakeholder group. J.E. is funded by an Australian National Health and Medical Research Council Practitioner Fellowship.

Author information

Affiliations

Authors

Contributions

All authors contributed to the design and drafting of the manuscript, and all authors agreed on the final version as submitted.

Corresponding author

Correspondence to Greg Rubin.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

PowerPoint slides

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Rubin, G., Walter, F., Emery, J. et al. Reimagining the diagnostic pathway for gastrointestinal cancer. Nat Rev Gastroenterol Hepatol 15, 181–188 (2018). https://doi.org/10.1038/nrgastro.2018.1

Download citation

Further reading