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Diagnostic performance of F-18 FDG PET/CT for prediction of KRAS mutation in colorectal cancer patients: a systematic review and meta-analysis

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Abstract

Objective

The purpose of the current study was to investigate the diagnostic performance of F-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) for the prediction of v-Ki-ras-2 Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation in colorectal cancer (CRC) patients through a systematic review and meta-analysis.

Methods

The PubMed and EMBASE database, from the earliest available date of indexing through April 30, 2018, were searched for studies evaluating the diagnostic performance of F-18 FDG PET/CT for prediction of KRAS mutation in CRC patients.

Results

Across 9 studies (804 patients), the pooled sensitivity for F-18 FDG PET/CT was 0.66 (95% CI 0.60–0.73) without heterogeneity (I2 = 34.1,p = 0.14) and a pooled specificity of 0.67 (95% CI 0.62–0.72) without heterogeneity (I2 = 1.63,p = 0.42). Likelihood ratio (LR) syntheses gave an overall positive likelihood ratio (LR+) of 2.0 (95% CI 1.7–2.4) and negative likelihood ratio (LR−) of 0.5 (95% CI 0.41–0.61). The pooled diagnostic odds ratio (DOR) was 4 (95% CI 3–6). Hierarchical summary receiver operating characteristic (ROC) curve indicates that the areas under the curve were 0.69 (95% CI 0.65–0.73).

Conclusion

The current meta-analysis showed the low sensitivity and specificity of F-18 FDG PET/CT for prediction of KRAS mutation in CRC patients. The DOR was very low and the likelihood ratio scatter-gram indicated that F-18 FDG PET/CT might not be useful for prediction of KRAS mutation and not for its exclusion. Therefore, cautious application and interpretation should be paid to the F-18 FDG PET/CT for prediction of KRAS mutation in CRC patients.

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References

  1. Siegel RL, Miller KD, Jemal A (2018) Cancer statistics, 2018 CA Cancer J Clin 68(1):7–30

    Article  Google Scholar 

  2. Pao W, Wang TY, Riely GJ, et al. (2005) KRAS mutations and primary resistance of lung adenocarcinomas to gefitinib or erlotinib. PLoS Med 2(1):e17

    Article CAS PubMed PubMed Central  Google Scholar 

  3. Eberhard DA, Johnson BE, Amler LC, et al. (2005) Mutations in the epidermal growth factor receptor and in KRAS are predictive and prognostic indicators in patients with non-small-cell lung cancer treated with chemotherapy alone and in combination with erlotinib. J Clin Oncol 23(25):5900–5909

    Article CAS PubMed  Google Scholar 

  4. Jonker DJ, O’Callaghan CJ, Karapetis CS, et al. (2007) Cetuximab for the treatment of colorectal cancer. N Engl J Med 357(20):2040–2048

    Article CAS PubMed  Google Scholar 

  5. Karapetis CS, Khambata-Ford S, Jonker DJ, et al. (2008) K-ras mutations and benefit from cetuximab in advanced colorectal cancers. N Engl J Med 359(17):1757–1765

    Article CAS PubMed  Google Scholar 

  6. Lievre A, Bachet JB, Boige V, et al. (2008) KRAS mutations as an independent prognostic factor in patients with advanced colorectal cancer treated with cetuximab. J Clin Oncol 26(3):374–379

    Article CAS PubMed  Google Scholar 

  7. Amado RG, Wolf M, Peeters M, et al. (2008) Wild-type KRAS is required for panitumumab efficiency in patients with metastatic colorectal cancer. J Clin Oncol 26(10):1626–1634

    Article CAS PubMed  Google Scholar 

  8. Conlin A, Smith G, Carey FA, Wolf CR, Steele RJ (2005) The prognostic significance of K-ras, p53, and APC mutations in colorectal carcinoma. Gut 54(9):1283–1286

    Article CAS PubMed PubMed Central  Google Scholar 

  9. Blodgett TM, Meltzer CC, Townsend DW (2007) PET/CT: form and function. Radiology 242(2):360–385

    Article PubMed  Google Scholar 

  10. Czernin J, Allen-Auerbach M, Schelbert HR (2007) Improvements in cancer staging with PET/CT: literature-based evidence as of September 2006. J Nucl Med 48(Suppl 1):78S–88S

    CAS PubMed  Google Scholar 

  11. Bar-Shalom R, Yefremov N, Guralnik L, et al. (2003) Clinical performance of PET/CT in evaluation of cancer: additional value for diagnostic imaging and patient management. J Nucl Med 44(8):1200–1209

    PubMed  Google Scholar 

  12. Lonneux M (2008) FDG-PET and PET/CT in Colorectal Cancer. PET Clin 3(2):147–153

    Article PubMed  Google Scholar 

  13. Yun J, Rago C, Cheong I, et al. (2009) Glucose deprivation contributes to the development of KRAS pathway mutations in tumor cells. Science 325(5947):1555-1559

    Article CAS PubMed PubMed Central  Google Scholar 

  14. Chen SW, Lin CY, Ho CM, et al. (2015) Genetic Alterations in Colorectal Cancer Have Different Patterns on18F-FDG PET/CT. Clin Nucl Med 40(8):621–626

    Article PubMed  Google Scholar 

  15. Oner AO, Budak ES, Yıldırım S, Aydın F, Sezer C (2017) The value of18FDG PET/CT parameters, hematological parameters and tumor markers in predicting KRAS oncogene mutation in colorectal cancer. Hell J Nucl Med 20(2):160-165

    PubMed  Google Scholar 

  16. Whiting PF, Rutjes AW, Westwood ME, et al. (2011) QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 155(8):529–536

    Article PubMed  Google Scholar 

  17. Glas AS, Lijmer JG, Prins MH, Bonsel GJ, Bossuyt PM (2003) The diagnostic odds ratio: a single indicator of test performance. J Clin Epidemiol 56(11):1129–1135

    Article PubMed  Google Scholar 

  18. Thompson SG (1994) Why sources of heterogeneity in meta-analysis should be investigated. BMJ 309(6965):1351–1355

    Article CAS PubMed PubMed Central  Google Scholar 

  19. Deeks JJ, Macaskill P, Irwig L (2005) The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. J Clin Epidemiol 58(9):882–893

    Article PubMed  Google Scholar 

  20. Hamza TH, van Houwelingen HC, Stijnen T (2008) The binomial distribution of meta-analysis was preferred to model within-study variability. J Clin Epidemiol 61(1):41–51

    Article PubMed  Google Scholar 

  21. Reitsma JB, Glas AS, Rutjes AW, Scholten RJ, Bossuyt PM, Zwinderman AH (2005) Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J Clin Epidemiol 58(10):982–990

    Article PubMed  Google Scholar 

  22. Rutter CM, Gatsonis CA (2001) A hierarchical regression approach to meta-analysis of diagnostic test accuracy evaluations. Stat Med 20(19):2865–2884

    Article CAS PubMed  Google Scholar 

  23. Lijmer JG, Mol BW, Heisterkamp S, et al. (1999) Empirical evidence of design-related bias in studies of diagnostic tests. JAMA 282(11):1061–1066

    Article CAS PubMed  Google Scholar 

  24. Stengel D, Bauwens K, Sehouli J, Ekkernkamp A, Porzsolt F (2003) A likelihood ratio approach to meta-analysis of diagnostic studies. J Med Screen 10(1):47–51

    Article CAS PubMed  Google Scholar 

  25. Leeflang MM, Deeks JJ, Gatsonis C & Bossuyt PM; Cochrane Diagnostic Test Accuracy Working Group (2008) Systematic Reviews of diagnostic test accuracy. Ann Intern Med 149(12):889–897

    Article  Google Scholar 

  26. Chen SW, Chiang HC, Chen WT, et al. (2014) Correlation between PET/CT parameters and KRAS expression in colorectal cancer. Clin Nucl Med 39(8):685–689

    Article PubMed  Google Scholar 

  27. Chen SW, Shen WC, Chen WT, et al. (2018) Metabolic Imaging Phenotype Using Radiomics of [18F]FDG PET/CT Associated with Genetic Alterations of Colorectal Cancer. Mol Imaging Biol 2018 Jun 12.https://doi.org/10.1007/s11307-018-1225-8. [Epub ahead of print]

  28. Cho A, Jo K, Hwang SH, et al. (2017) Correlation between KRAS mutation and18F-FDG uptake in stage IV colorectal cancer. Abdom Radiol (NY) 42(6):1621–1626

    Article  Google Scholar 

  29. Kawada K, Nakamoto Y, Kawada M, et al. (2012) Relationship between 18F-Fluorodeoxyglucose accumulation and KRAS/BRAF mutations in colorectal cancer. Clin Cancer Res 18(6):1696–1703

    Article CAS PubMed  Google Scholar 

  30. Kawada K, Toda K, Nakamoto Y, et al. (2015) Relationship Between18F-FDG PET/CT Scans and KRAS Mutations in Metastatic Colorectal Cancer. J Nucl Med 56(9):1322–1327

    Article CAS PubMed  Google Scholar 

  31. Krikelis D, Skoura E, Kotoula V, et al. (2014) Lack of association between KRAS mutations and18F-FDG PET/CT in Caucasian metastatic colorectal cancer patients. Anticancer Res 34(5):2571–2579

    PubMed  Google Scholar 

  32. Lee JH, Kang J, Baik SH, et al. (2016) Relationship Between 18F-Fluorodeoxyglucose Uptake and V-Ki-Ras2 Kirsten Rat Sarcoma Viral Oncogene Homolog Mutation in Colorectal Cancer Patients: Variability Depending on C-Reactive Protein Level. Medicine (Baltimore) 95(1):e2236

    Article CAS  Google Scholar 

  33. Lovinfosse P, Koopmansch B, Lambert F, et al. (2016)18F-FDG PET/CT imaging in rectal cancer: relationship with the RAS mutational status. Br J Radiol 89(1063):20160212

    Article PubMed PubMed Central  Google Scholar 

  34. Mao W, Zhou J, Zhang H, et al. (2018) Relationship between KRAS mutations and dual time point 18F-FDG PET/CT imaging in colorectal liver metastases. Abdom Radiol (NY) 2018 Aug 24.https://doi.org/10.1007/s00261-018-1740-8. [Epub ahead of print]

  35. Forrester K, Almoguera C, Han K, Grizzle WE, Perucho M (1987) Detection of high incidence of K-ras oncogenes during human colon tumorigenesis. Nature 327(6120):298–303

  36. Caicedo C, Garcia-Velloso MJ, Lozano MD, et al. (2014) Role of [18F]FDG PET in prediction of KRAS and EGFR mutation status in patients with advanced non-small-cell lung cancer. Eur J Nucl Med Mol Imaging 41(11):2058–2065

    Article CAS PubMed  Google Scholar 

  37. Jadvar H, Alavi A, Gambhir SS (2009)18F-FDG uptake in lung, breast, and colon cancers: molecular biology correlates and disease characterization. J Nucl Med 50(11):1820–1827

    Article PubMed PubMed Central  Google Scholar 

  38. Lee SM, Bae SK, Jung SJ, Kim CK (2015) FDG uptake in non-small cell lung cancer is not an independent predictor of EGFR or KRAS mutation status: a retrospective analysis of 206 patients. Clin Nucl Med 40(12):950–958

    Article PubMed  Google Scholar 

  39. Takamochi K, Mogushi K, Kawaji H, et al. (2017) Correlation of EGFR or KRAS mutation status with18F-FDG uptake on PET-CT scan in lung adenocarcinoma. PLoS One 12(4):e0175622

    Article CAS PubMed PubMed Central  Google Scholar 

  40. Ikeno Y, Seo S, Iwaisako K, et al. (2018) Preoperative metabolic tumor volume of intrahepatic cholangiocarcinoma measured by18F-FDG-PET is associated with the KRAS mutation status and prognosis. J Transl Med 16(1):95

    Article CAS PubMed PubMed Central  Google Scholar 

Download references

Funding

This research did not receive any specific grant from any funding agency in the public, commercial, or not-for-profit sector.

Author information

Authors and Affiliations

  1. Department of Nuclear Medicine, College of Medicine, Pusan National University Yangsan Hospital, Yangsan, 50612, South Korea

    Seong-Jang Kim

  2. BioMedical Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, 50612, South Korea

    Seong-Jang Kim

  3. Department of Nuclear Medicine, Pusan National University Hospital, Busan, South Korea

    Kyoungjune Pak & Keunyoung Kim

Authors
  1. Seong-Jang Kim

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  2. Kyoungjune Pak

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Contributions

Kim SJ and Pak K contributed in protocol/project development. Kim SJ, Kim K, and Pak K contributed in data collection or management. Kim SJ and Kim K contributed in data analysis. Kim SJ, Pak K, and Kim K contributed in manuscript writing/editing.

Corresponding author

Correspondence toSeong-Jang Kim.

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Conflict of interest

The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of this study.

Ethical approval

Institutional review board approval was not required because we only performed data analysis based on the published studies.

Informed consent

Written informed consent was not required for this study because it is a meta-analysis based on the studies that have been published.

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Kim, SJ., Pak, K. & Kim, K. Diagnostic performance of F-18 FDG PET/CT for prediction of KRAS mutation in colorectal cancer patients: a systematic review and meta-analysis.Abdom Radiol44, 1703–1711 (2019). https://doi.org/10.1007/s00261-018-01891-3

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