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Diagnostic accuracy of panoramic radiography in the detection of calcified carotid artery atheroma: a meta-analysis

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Abstract

Objective

To determine the diagnostic accuracy of panoramic radiography (PR) in detecting calcified carotid artery atheroma (CCAA) compared with Doppler ultrasonography or angiography (the reference standard).

Sources

Cochrane, LILACS, PubMed, Scopus, Web of Science, Google Scholar, Open Grey, and ProQuest were searched. The reference lists of the included studies were also screened.

Data

Observational studies.

Methods

Only studies comparing the diagnostic accuracy of PR in detecting CCAA to Doppler ultrasonography or angiography (the reference standard) were included. The primary outcome measures were sensitivity and specificity. The secondary outcomes were negative predictive values, positive predictive values, diagnostic odds ratios, likelihood ratios (positive and negative), receiver operating characteristic curves, accuracy, and Youden’s index. Two reviewers independently participated in the study selection, data extraction, and risk of bias assessment without language restriction. Risk of bias was assessed thought QUADAS-2, and the level of evidence was assessed through GRADE.

Results

A total of 773 citations were identified after duplicates were removed, and 12 studies including 1002 patients were included in the final study. The sensitivity and specificity of the different selected studies varied substantially, with sensitivity ranging from 0.31 to 0.95 and specificity from 0.19 to 0.99.

Conclusions

Most studies reported excellent sensitivity and good specificity. The diagnostic accuracy of PR was good or excellent in 50% of the studies.

Clinical significance

The identification of CCAA by PR can be a risk predictor for stroke when used as a secondary screening tool.

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References

  1. Bonita R, Beaglehole R (1993) Explaining stroke mortality trends. Lancet 341(8859):1510–1511

    Article  PubMed  Google Scholar 

  2. Baumann-Bhalla S, Meier RM, Burow A, Lyrer P, Engelter S, Bonati L, Filippi A, Lambrecht JT (2012) Recognizing calcifications of the carotid artery on panoramic radiographs to prevent strokes. Schweiz Monatssch Zahnmed 122(11):1016–1029

    Google Scholar 

  3. Friedlander AH (1995) Identification of stroke-prone patients by panoramic and cervical spine radiography. Dentomaxillofac Radiol 24(3):160–164. https://doi.org/10.1259/dmfr.24.3.8617388

    Article  PubMed  Google Scholar 

  4. Friedlander AH, Baker JD (1994) Panoramic radiography: an aid in detecting patients at risk of cerebrovascular accident. J Am Dent Assoc 125(12):1598–1603

    Article  PubMed  Google Scholar 

  5. Bayram B, Uckan S, Acikgoz A, Müderrisoǧlu H, Aydinalp A (2006) Digital panoramic radiography: a reliable method to diagnose carotid artery atheromas? Dentomaxillofac Radiol 35(4):266–270. https://doi.org/10.1259/dmfr/50195822

    Article  PubMed  Google Scholar 

  6. Almog DM, Illig KA, Khin M, Green RM (2000) Unrecognized carotid artery stenosis discovered by calcifications on a panoramic radiograph. J Am Dent Assoc 131(11):1593–1597

    Article  PubMed  Google Scholar 

  7. Friedlander AH, Lande A (1981) Panoramic radiographic identification of carotid arterial plaques. Oral Surg Oral Med Oral Pathol 52(1):102–104. https://doi.org/10.1016/0030-4220(81)90181-X

    Article  PubMed  Google Scholar 

  8. Pornprasertsuk-Damrongsri S, Virayavanich W, Thanakun S, Siriwongpairat P, Amaekchok P, Khovidhunkit W (2009) The prevalence of carotid artery calcifications detected on panoramic radiographs in patients with metabolic syndrome. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 108(4):57–62. https://doi.org/10.1016/j.tripleo.2009.05.021

    Article  Google Scholar 

  9. Christou P, Leemann B, Schimmel M, Kiliaridis S, Muller F (2010) Carotid artery calcification in ischemic stroke patients detected in standard dental panoramic radiographs—a preliminary study. Adv Med Sci 55(1):26–31. https://doi.org/10.2478/v10039-010-0022-7

    Article  PubMed  Google Scholar 

  10. Friedlander AH (1995) Panoramic radiography: the differential diagnosis of carotid artery atheromas. Spec Care Dentist 15(6):223–227

    Article  PubMed  Google Scholar 

  11. Mupparapu M, Kim IH (2007) Calcified carotid artery atheroma and stroke: a systematic review. J Am Dent Assoc (1939) 138(4):483–492

    Article  Google Scholar 

  12. Shamseer L, Moher D, Clarke M, Ghersi D, Liberati A, Petticrew M, Shekelle P, Stewart LA, Group P-P (2015) Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ 350:g7647. https://doi.org/10.1136/bmj.g7647

    Article  PubMed  Google Scholar 

  13. Moher D, Liberati A, Tetzlaff J, Altman DG, Group P (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Open Med 3(3):e123–e130

    PubMed  PubMed Central  Google Scholar 

  14. Whiting P, Rutjes AW, Reitsma JB, Bossuyt PM, Kleijnen J (2003) The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol 3:25. https://doi.org/10.1186/1471-2288-3-25

    Article  PubMed  PubMed Central  Google Scholar 

  15. GRADE (2014) Grading of recommendations assessment d, evaluation a. GRADE. Grading of Recommendations Assessment, Development and Evaluation

  16. Imanimoghaddam M, Rah Rooh M, Mahmoudi Hashemi E, Javadzade Blouri A (2012) Doppler sonography confirmation in patients showing calcified carotid artery atheroma in panoramic radiography and evaluation of related risk factors. J Dent Res Dent Clin Dent Prospects 6(1):6–11. https://doi.org/10.5681/joddd.2012.002

    Article  PubMed  PubMed Central  Google Scholar 

  17. Romano-Sousa CM, Krejci L, Medeiros FMM, Graciosa-Filho RG, Martins MFF, Guedes VN, Fenyo-Pereira M (2009) Diagnostic agreement between panoramic radiographs and color doppler images of carotid atheroma. J Appl Oral Sci 17(1):45–48. https://doi.org/10.1590/S1678-77572009000100009

    Article  PubMed  PubMed Central  Google Scholar 

  18. Bastos JS, Abreu TQ, Filho SBB, de Sales KPF, Lopes FF, de Oliveira AEF (2012) Sensitivity and accuracy of panoramic radiography in identifying calcified carotid atheroma plaques. Braz J Oral Sci 11(2):88–93

    Google Scholar 

  19. Damaskos S, Griniatsos J, Tsekouras N, Georgopoulos S, Klonaris C, Bastounis E, Tsiklakis K (2008) Reliability of panoramic radiograph for carotid atheroma detection: a study in patients who fulfill the criteria for carotid endarterectomy. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 106(5):736–742. https://doi.org/10.1016/j.tripleo.2008.03.039

    Article  PubMed  Google Scholar 

  20. Khambete N, Kumar R, Risbud M, Joshi A (2012) Evaluation of carotid artery atheromatous plaques using digital panoramic radiographs with Doppler sonography as the ground truth. J Oral Biol Craniofac Res 2(3):149–153. https://doi.org/10.1016/j.jobcr.2012.10.005

    Article  PubMed  PubMed Central  Google Scholar 

  21. Yeluri G, Kumar CA, Raghav N (2015) Correlation of dental pulp stones, carotid artery and renal calcifications using digital panoramic radiography and ultrasonography. Contemp Clin Dent 6:S147–S151. https://doi.org/10.4103/0976-237X.166837

    Article  PubMed  PubMed Central  Google Scholar 

  22. Khosropanah SH, Shahidi SH, Bronoosh P, Rasekhi A (2009) Evaluation of carotid calcification detected using panoramic radiography and carotid Doppler sonography in patients with and without coronary artery disease. Br Dental J 207(4):162–163. https://doi.org/10.1038/sj.bdj.2009.762

    Article  Google Scholar 

  23. Abecasis P, Chimenos-Kustner E, Lopez-Lopez O (2014) Orthopantomography contribution to prevent isquemic stroke. J Clin Exp Dent 6(2):e127–e131. https://doi.org/10.4317/jced.51352

    Article  PubMed  PubMed Central  Google Scholar 

  24. Pornprasertsuk-Damrongsri S, Virayavanich W, Thanakun S, Siriwongpairat P, Amaekchok P, Khovidhunkit W (2011) Carotid atheroma detected by panoramic radiography and ultrasonography in patients with metabolic syndrome. Oral Radiol 27(1):43–49. https://doi.org/10.1007/s11282-011-0064-y

    Article  Google Scholar 

  25. Ertas ET, Sisman Y (2011) Detection of incidental carotid artery calcifications during dental examinations: panoramic radiography as an important aid in dentistry. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 112(4):e11–e17. https://doi.org/10.1016/j.tripleo.2011.02.048

    Article  PubMed  Google Scholar 

  26. Alman AC, Johnson LR, Calverley DC, Grunwald GK, Lezotte DC, Hokanson JE (2013) Validation of a method for quantifying carotid artery calcification from panoramic radiographs. Oral Surg Oral Med Oral Pathol Oral Radiol 116(4):518–524. https://doi.org/10.1016/j.oooo.2013.06.026

    Article  PubMed  Google Scholar 

  27. Madden RP, Hodges JS, Salmen CW, Rindal DB, Tunio J, Michalowicz BS, Ahmad M (2007) Utility of panoramic radiographs in detecting cervical calcified carotid atheroma. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 103(4):543–548. https://doi.org/10.1016/j.tripleo.2006.06.048

    Article  PubMed  Google Scholar 

  28. De Luca Canto G, Pacheco-Pereira C, Aydinoz S, Major PW, Flores-Mir C, Gozal D (2015) Diagnostic capability of biological markers in assessment of obstructive sleep apnea: a systematic review and meta-analysis. J Clin Sleep Med 11(1):27–36. https://doi.org/10.5664/jcsm.4358

    Article  PubMed  PubMed Central  Google Scholar 

  29. Bengtsson VW, Persson GR, Berglund J, Renvert S (2018) Carotid calcifications in panoramic radiographs are associated with future stroke or ischemic heart diseases: a long-term follow-up study. Clin Oral Investig. https://doi.org/10.1007/s00784-018-2533-8

  30. Almog DM, Horev T, Illig KA, Green RM, Carter LC (2002) Correlating carotid artery stenosis detected by panoramic radiography with clinically relevant carotid artery stenosis determined by duplex ultrasound. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 94(6):768–773. https://doi.org/10.1067/moe.2002.128965

    Article  PubMed  Google Scholar 

  31. Veiga Abecasis P, Chimenos-Kustner E (2012) Can orthopantomography be used as a tool for screening of carotid atheromatous pathology and thus be used to help reduce the prevalence of ischemic stroke within the population? J Clin Exp Dent 4(1):e19–e22

    Article  PubMed  PubMed Central  Google Scholar 

  32. Abreu TQ, Ferreira EB, de Brito Filho SB, de Sales KPF, Lopes FF, de Oliveira AEF (2015) Prevalence of carotid artery calcifications detected on panoramic radiographs and confirmed by Doppler ultrasonography: their relationship with systemic conditions. Indian J Dent Res 26(4):345–350

    Article  PubMed  Google Scholar 

  33. Almog DM (2007) Utility of panoramic radiographs in detecting cervical calcified carotid atheroma. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 104(4):451

    Article  PubMed  Google Scholar 

  34. Atalay Y, Asutay F, Agacayak KS et al (2015) Evaluation of calcified carotid atheroma on panoramic radiographs and Doppler ultrasonography in an older population. Clin Interv Aging 10:1121–1129

    Article  PubMed  PubMed Central  Google Scholar 

  35. Deahl Ii ST (2007) Panoramic radiography does not reliably detect carotid artery calcification nor stenosis. Journal of Evidence-Based Dental Practice 7(4):172–173

    Article  Google Scholar 

  36. Doris I, Dobranowski J, Franchetto AA, Jaeschke R (1993) The relevance of detecting carotid artery calcification on plain radiograph. Stroke 24(9):1330–1334

    Article  PubMed  Google Scholar 

  37. Friedlander A, Chang TI, Aghazadehsanai N, Berenji GR, Harada ND, Garrett NR (2013) Panoramic images of white and black post-menopausal females evidencing carotid calcifications are at high risk of comorbid osteopenia of the femoral neck. Dentomaxillofac Radiol 42(5):20120195

    Article  PubMed  PubMed Central  Google Scholar 

  38. Friedlander AH, Garrett MR, Chin EE, Baker JD (2005) Ultrasonographic confirmation of carotid artery atheromas diagnosed via panoramic radiography. J Am Dent Assoc 136(5):635–640

    Article  PubMed  Google Scholar 

  39. Friedlander AH, Liebeskind DS, Tran HQ, Mallya SM (2014) What are the potential implications of identifying intracranial internal carotid artery atherosclerotic lesions on cone-beam computed tomography? A systematic review and illustrative case studies. J Oral Maxillofac Surg 72(11):2167–2177

    Article  PubMed  Google Scholar 

  40. Garoff M, Ahlqvist J, Jaghagen EL, Johansson E, Wester P (2016) Carotid calcification in panoramic radiographs: radiographic appearance and the degree of carotid stenosis. Dentomaxillofac Radiol 45(6):20160147

    Article  PubMed  PubMed Central  Google Scholar 

  41. Garoff M, Johansson E, Ahlqvist J, Arnerlöv C, Levring Jäghagen E, Wester P (2015) Calcium quantity in carotid plaques: detection in panoramic radiographs and association with degree of stenosis. Oral Surg Oral Med Oral Pathol Oral Radiol 120(2):269–274

    Article  PubMed  Google Scholar 

  42. Garoff M, Johansson E, Ahlqvist J, Jäghagen EL, Arnerlöv C, Wester P (2014) Detection of calcifications in panoramic radiographs in patients with carotid stenoses ≥ 50%. Oral Surg Oral Med Oral Pathol Oral Radiol 117(3):385–391

    Article  PubMed  Google Scholar 

  43. Gouvea AF, Vargas PA, Jorge J, Lopes MA (2009) Using panoramic radiographs to detect carotid artery calcifications: are they a helpful diagnostic tool? Gen Dent 57(5):480–484

    PubMed  Google Scholar 

  44. Griniatsos J, Damaskos S, Tsekouras N, Klonaris C, Georgopoulos S (2009) Correlation of calcified carotid plaques detected by panoramic radiograph with risk factors for stroke development. Oral Surg Oral Med Oral Pathol Oral Radiol Endodontol 108(4):600–603

    Article  Google Scholar 

  45. Hoke M, Schmidt B, Schillinger T et al (2010) Evidence of carotid atherosclerosis in orthopantomograms and the risk for future cardiovascular events. Vasa 39(4):298–304

    Article  PubMed  Google Scholar 

  46. Johansson E, Ahlqvist J, Garoff M et al (2011) Ultrasound screening for asymptomatic carotid stenosis in subjects with calcifications in the area of the carotid arteries on panoramic radiographs: a cross-sectional study. BMC Cardiovasc Disord 11

  47. Johansson E, Ahlqvist J, Garoff M, Levring Jäghagen E, Meimermondt A, Wester P (2015) Carotid calcifications on panoramic radiographs: a 5-year follow-up study. Oral Surg Oral Med Oral Pathol Oral Radiol 120(4):513–520

    Article  PubMed  Google Scholar 

  48. Kansu Ö, Özbek M, Avcu N, Gençtoy G, Kansu H, Turgan Ç (2005) The prevalence of carotid artery calcification on the panoramic radiographs of patients with renal disease. Dentomaxillofac Radiol 34(1):16–19

    Article  PubMed  Google Scholar 

  49. Khambete N, Kumar R, Risbud M, Joshi A (2014) Reliability of digital panoramic radiographs in detecting calcified carotid artery atheromatous plaques: a clinical study. Indian J Dent Res 25(1):36–40

    Article  PubMed  Google Scholar 

  50. Lee JS, Kim OS, Chung HJ, Kim YJ, Kweon SS, Lee YH, Shin MH, Yoon SJ (2014) The correlation of carotid artery calcification on panoramic radiographs and determination of carotid artery atherosclerosis with ultrasonography. Oral Surg Oral Med Oral Pathol Oral Radiol 118(6):739–745

    Article  PubMed  Google Scholar 

  51. Ravon NA, Hollender LG, McDonald V, Persson GR (2003) Signs of carotid calcification from dental panoramic radiographs are in agreement with Doppler sonography results. J Clin Periodontol 30(12):1084–1090

    Article  PubMed  Google Scholar 

  52. Shetty RR (2015) Aid of a digital orthopantomogram in the detection of carotid atheromas. J Evol Med Dent Sci-JEMDS 4(56):9810–9818

    Google Scholar 

  53. Tofangchiha M, Marami A, Mosallaei SS, Moghaddam AA (2009) Comparison of panoramic radiography in detection of carotid artery calcifications with Doppler sonography results. J Qazvin Univ Med Sci 13:63–67

    Google Scholar 

  54. Uchida K, Sugino N, Yamada S, Kuroiwa H, Yoshinari N, Asano A, Taguchi A, Muneyasu M (2014) Clinical significance of carotid artery calcification seen on panoramic radiographs. J Hard Tissue Biol 23(4):461–466

    Article  Google Scholar 

  55. Yoon SJ, Yoon W, Kim OS, Lee JS, Kang BC (2008) Diagnostic accuracy of panoramic radiography in the detection of calcified carotid artery. Dentomaxillofac Radiol 37(2):104–108

    Article  PubMed  Google Scholar 

  56. Simundic AM (2009) Measures of diagnostic accuracy: basic definitions. EJIFCC 19(4):203–211

    PubMed  PubMed Central  Google Scholar 

  57. 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 

  58. Deeks JJ, Bossuyt P, Gatsonis C (eds) (2010) Cochrane handbook for systematic reviews of diagnostic test accuracy version 1.0. The Cochrane Collaboration. Available from: http://srdta.cochrane.org/. Accessed 10 Dec 2017

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Author information

Authors and Affiliations

  1. Department of Dentistry, Pontifícia Universidade Católica do Paraná, Curitiba, PR, Brazil

    Angela Graciela Deliga Schroder

  2. Department of Orthodontics, Pontifícia Universidade Católica do Paraná, Curitiba, PR, Brazil

    Cristiano Miranda de Araujo & Odilon Guariza-Filho

  3. School of Health and Bioscience, Department of orthodontics, Pontifícia Universidade Católica do Paraná, Street Imaculada Conceição, 1155, Prado Velho, Curitiba, PR, 80215-901, Brazil

    Odilon Guariza-Filho

  4. School of Dentistry, University of Alberta, Alberta, Canada

    Carlos Flores-Mir

  5. Brazilian Centre for Evidence-based Research, Department of Dentistry, Federal University of Santa Catarina, Florianópolis, SC, Brazil

    Graziela de Luca Canto

  6. Brazilian Centre for Evidence-based Research, Department of Dentistry, Federal University of Santa Catarina, Florianópolis, SC, Brazil

    André Luís Porporatti

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  1. Angela Graciela Deliga Schroder
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  2. Cristiano Miranda de Araujo
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  3. Odilon Guariza-Filho
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  4. Carlos Flores-Mir
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  5. Graziela de Luca Canto
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  6. André Luís Porporatti
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Corresponding author

Correspondence to Odilon Guariza-Filho.

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Appendices

Appendix 1 Search

Table 4 Database search strategy
Full size table

Appendix 2

Table 5 Excluded articles and reasons for exclusion (n = 34)
Full size table

Appendix 3 Pooled Results

Summary sensitivity

Study

Sen

(95% conf. interval)

TP/(TP + FN)

TN/(TN + FP)

Abecasis, P.V., Kust

0.778

0.577–0.914

21/27

23/27

Alman, A.C. et al.

0.771

0.599–0.896

27/35

72/86

Bastos, J.S. et al.

0.739

0.516–0.898

17/23

7/19

Damakos, S. et al.

0.609

0.454–0.749

28/46

16/34

Ertas, E.T., Sisman

0.798

0.708–0.870

83/104

86/106

Khambete, N. et al.

0.760

0.549–0.906

19/25

74/75

Imanimoghaddam, M. et al.

0.875

0.617–0.984

14/16

3/14

Madden, R.P. et al.

0.308

0.199–0.434

20/65

34/39

Khosropanah, S.H. et al.

0.500

0.211–0.789

6/12

23/32

Romano-Sousa, C.M. et al.

0.950

0.751–0.999

19/20

9/12

Pornprasertsuk-Damro

0.864

0.651–0.971

19/22

31/63

Yeluri, G. et al.

0.937

0.858–0.979

74/79

4/21

Pooled Sen

0.732

0.690–0.771

  
  1. Heterogeneity chi-squared = 92.89 (d.f. = 11) p = 0.000
  2. Inconsistency (I-square) = 88.2%
  3. No. of studies = 12
  4. Filter OFF
  5. Add 1/2 to all cells of the studies with zero

Summary specificity

Study

Spe

(95% conf. interval)

TP/(TP + FN)

TN/(TN + FP)

Abecasis, P.V., Kust

0.852

0.663–0.958

21/27

23/27

Alman, A.C. et al.

0.837

0.742–0.908

27/35

72/86

Bastos, J.S. et al.

0.368

0.163–0.616

17/23

7/19

Damakos, S. et al.

0.471

0.298–0.649

28/46

16/34

Ertas, E.T., Sisman

0.811

0.724–0.881

83/104

86/106

Khambete, N. et al.

0.987

0.928–1000

19/25

74/75

Imanimoghaddam, M. et al.

0.214

0.047–0.508

14/16

3/14

Madden, R.P. et al.

0.872

0.726–0.957

20/65

34/39

Khosropanah, S.H. et al.

0.719

0.533–0.863

6/12

23/32

Romano-Sousa, C.M. et al.

0.750

0.428–0.945

19/20

9/12

Pornprasertsuk-Damro

0.492

0.364–0.621

19/22

31/63

Yeluri, G. et al.

0.190

0.054–0.419

74/79

4/21

Pooled Spe

0.723

0.683–0.761

  
  1. Heterogeneity chi-squared = 134.56 (d.f. = 11) p = 0.000
  2. Inconsistency (I-square) = 91.8%
  3. No. of studies = 12
  4. Filter OFF
  5. Add 1/2 to all cells of the studies with zero

Summary positive likelihood ratio (random effects model)

Study

LR+

(95% conf. interval)

% weight

Abecasis, P.V., Kust

5.250

2.078–13.262

7.12

Alman, A.C. et al.

4.739

2.840–7.908

9.11

Bastos, J.S. et al.

1.170

0.768–1.782

9.49

Damakos, S. et al.

1.150

0.776–1.703

9.59

Ertas, E.T., Sisman

4.230

2.817–6.351

9.54

Khambete, N. et al.

57.000

8.035–404.37

3.40

Imanimoghaddam, M. et al.

1.114

0.800–1.550

9.81

Madden, R.P. et al.

2.400

0.980–5.879

7.27

Khosropanah, S.H. et al.

1.778

0.805–3.924

7.78

Romano-Sousa, C.M. et al.

3.800

1.419–10.177

6.84

Pornprasertsuk-Damro

1.700

1.267–2.282

9.92

Yeluri, G.et al.

1.157

0.933–1.435

10.13

(REM) pooled LR+

2.319

1.492–3.603

 
  1. Heterogeneity chi-squared = 119.39 (d.f. = 11) p = 0.000
  2. Inconsistency (I-square) = 90.8%
  3. Estimate of between-study variance (Tau-squared) = 0.4874
  4. No. of studies = 12
  5. Filter OFF
  6. Add 1/2 to all cells of the studies with zero

Summary negative likelihood ratio (random effects model)

Study

LR−

(95% conf. interval)

% weight

Abecasis, P.V., Kust

0.261

0.127–0.538

9.05

Alman, A.C. et al.

0.273

0.147–0.505

9.63

Bastos, J.S. et al.

0.708

0.286–1751

8.06

Damakos, S. et al.

0.832

0.501–1381

10.18

Ertas, E.T., Sisman

0.249

0.168–0.369

10.69

Khambete, N. et al.

0.243

0.121–0.489

9.19

Imanimoghaddam, M. et al.

0.583

0.113–3005

4.76

Madden, R.P. et al.

0.794

0.649–0.972

11.33

Khosropanah, S.H. et al.

0.696

0.380–1275

9.68

Romano-Sousa, C.M. et al.

0.067

0.010–0.463

3.86

Pornprasertsuk-Damro

0.277

0.094–0.817

7.13

Yeluri, G. et al.

0.332

0.098–1130

6.44

(REM) pooled LR−

0.396

0.249–0.632

 
  1. Heterogeneity chi-squared = 73.40 (d.f. = 11) p = 0.000
  2. Inconsistency (I-square) = 85.0%
  3. Estimate of between-study variance (Tau-squared) = 0.4887
  4. No. of studies = 12
  5. Filter OFF
  6. Add 1/2 to all cells of the studies with zero

Summary diagnostic odds ratio (random effects model)

Study

DOR

(95% conf. interval)

% weight

Abecasis, P.V., Kust

20.125

4.980–81.336

8.35

Alman, A.C. et al.

17.357

6.548 –46.007

9.74

Bastos, J.S. et al.

1.653

0.443–6170

8.61

Damakos, S. et al.

1.383

0.564–3390

9.98

Ertas, E.T., Sisman

16.995

8.588–33.634

10.59

Khambete, N. et al.

234.33

26.590–2065.1

5.98

Imanimoghaddam, M. et al.

1.909

0.270–13.495

6.59

Madden, R.P. et al.

3.022

1.030–8.868

9.41

Khosropanah, S.H. et al.

2.556

0.650–10.048

8.44

Romano-Sousa, C.M. et al.

57.000

5.181–627.14

5.42

Pornprasertsuk-Damro

6.135

1.649–22.830

8.62

Yeluri, G.et al.

3.482

0.845–14.357

8.28

(REM) pooled DOR

6.923

3.220–14.884

 
  1. Heterogeneity chi-squared = 49.22 (d.f. = 11) p = 0.000
  2. Inconsistency (I-square) = 77.7%
  3. Estimate of between-study variance (Tau-squared) = 13.194
  4. No. of studies = 12
  5. Filter OFF
  6. Add 1/2 to all cells of the studies with zero

Analysis of diagnostic threshold

Spearman correlation coefficient: 0.364 p value = 0.245

(Logit(TPR) vs Logit(FPR)

Moses’ model (D = a + bS)

Weighted regression (inverse variance)

Var

Coeff.

Std. error

T

p value

a

2.042

0.406

5033

0.0005

b(1)

− 0.261

0.196

1332

0.2126

  1. Tau-squared estimate = 13.891 (convergence is achieved after six iterations)
  2. Restricted maximum likelihood estimation (REML)
  3. No. of studies = 12
  4. Filter OFF
  5. Add 1/2 to all cells of the studies with zero

Appendix 4 Test indicators

Test indicators

Data analysis

References

Accuracy

Accuracy (effectiveness) is affected by the disease prevalence. This percentage of correctly classified subjects should always be weighed considering other measures of diagnostic accuracy, especially predictive values.

Simundic [56]

DOR

The value of a DOR ranges from 0 to infinity, with higher values indicating better discriminatory test performance. A value of 1 means that a test does not discriminate between patients with the disorder and those without it. Values lower than 1 point to improper test interpretation (more negative tests among the diseased).

Glas et al. [57]

LR

LR tells us how many times more likely particular test result is in subjects with the disease than in those without disease.

LR+ > 3 and an LR− < 0.3—acceptable diagnostic test accuracy (DTA)

LR+ > 10 and LR− < 0.1—excellent DTA.

Simundic [56]

Predictive values

PPV and NPV are largely dependent on disease prevalence in examined population, therefore, predictive values from on study should not be transferred to some other setting with a different prevalence of the disease in the population.

Simundic [56]

ROC curve

The shape of a ROC curve and the area under the curve (AUC) helps us estimate how high is the discriminative power of a test. The closer the curve is located to upper-left hand corner and the larger the area under the curve, the better the test is at discriminating between diseased and nondiseased. The area under the curve can have any value between 0 and 1 and it is a good indicator of the goodness of the test. A perfect diagnostic test has an AUC 1.0. whereas a nondiscriminating test has an area 0.5.

Simundic [56]

Sensitivity

Sensitivity > 80% excellent, 70–80% good, 60–69% fair, < 60% poor, no consensus in this regard exists in the literature.

No consensus in this regard exists in the literature.

Specificity

Specificity > 90% excellent, 80–90% good, 70–79% fair, < 70% poor, no consensus in this regard exists in the literature.

No consensus in this regard exists in the literature.

Youden’s

index

Youden’s index values close to 1 indicate high accuracy; a value of zero is equivalent to uninformed guessing and indicates that a test has no diagnostic value.

Deeks et al. [58]

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Schroder, A.G.D., de Araujo, C.M., Guariza-Filho, O. et al. Diagnostic accuracy of panoramic radiography in the detection of calcified carotid artery atheroma: a meta-analysis. Clin Oral Invest 23, 2021–2040 (2019). https://doi.org/10.1007/s00784-019-02880-6

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