Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

The Collaborative Ocular Tuberculosis Study (COTS) calculator—a consensus-based decision tool for initiating antitubercular therapy in ocular tuberculosis

Abstract

Objective

To introduce the Collaborative Ocular Tuberculosis Study (COTS) Calculator, an online clinical scoring system for initiating antitubercular therapy (ATT) in patients with ocular tuberculosis (TB).

Method

The COTS Calculator was derived from COTS Consensus (COTS CON) data, which has previously published consensus guidelines. Using a two-step Delphi method, 81 experts evaluated 486 clinical scenario-based questions, ranking their likelihood of initiating ATT in each specific scenario. Each scenario was a permutation of the results and/or availability of five following components—clinical phenotype, endemicity, two immunological (tuberculin skin test, interferon-γ release assay) and one radiological (chest X-Ray) test results—and a sixth component further stratifying three of the clinical phenotypes. The median scores and interquartile ranges (IQR) of each scenario were tabulated, representing the expert consensus on whether to initiate ATT in that scenario. The consensus table was encoded to develop the COTS Calculator.

Results

The COTS Calculator can be accessed online at: https://www.oculartb.net/cots-calc. The attending physician can select the conditions present in the patient, which will generate a median score from 1 to 5. 114 out of 486 scenarios (24%) deliberated had a median score of 5 indicating expert consensus to initiate ATT.

Conclusion

The COTS Calculator is an efficient, low-cost, evidence and experience-based clinical tool to guide ATT initiation. While it holds substantial promise in improving standard-of-care for ocular-TB patients, future validation studies can help to as certain its clinical utility and reliability.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Flow chart depicting the number of clinical scenario-based questions reviewed in the Collaborative Ocular Tuberculosis Study Consensus (COTS CON) group Delphi Round 1 and 2, the clinical phenotypes reviewed in Delphi Round 2 phases 1 and 2, as well as the number of experts attending each discussion phase.
Fig. 2: Diagrammatic illustration of the ordinal score as entered by the experts and implication of median score and interquartile range (IQR).
Fig. 3: The patient details that can be entered include patient name, patient identity document (ID) number, patient’s age, patient’s gender (male or female), patient’s physician name, the patient’s affected eye (left, right, or both eyes).
Fig. 4: The clinical phenotype selected is “retinal vasculitis” out of five options (anterior uveitis, intermediate uveitis, panuveitis, retinal vasculitis, choroiditis), which prompted an additional stratification of “active” disease to be selected amongst two options (active, inactive).

Similar content being viewed by others

Data availability

The datasets generated during and/or analysed during the current study are not publicly available. Nevertheless, interested researchers are invited to direct data access requests to the corresponding author.

References

  1. World Health Organization. Global Tuberculosis Report. 2021. https://www.who.int/publications/i/item/9789240037021.

  2. Bouza E, Merino P, Muñoz P, Sanchez-Carrillo C, Yáñez J, Cortés C. Ocular tuberculosis. A prospective study in a general hospital. Medicine 1997;76:53–61.

    Article  CAS  PubMed  Google Scholar 

  3. Biswas J, Badrinath SS. Ocular morbidity in patients with active systemic tuberculosis. Int Ophthalmol. 1995;19:293–8.

    Article  PubMed  Google Scholar 

  4. Basu S, Monira S, Modi RR, Choudhury N, Mohan N, Padhi TR, et al. Degree, duration, and causes of visual impairment in eyes affected with ocular tuberculosis. J Ophthalmic Inflamm Infect. 2014;4:3.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Shah JS, Shetty N, Shah SK, Shah NK. Tubercular uveitis with ocular manifestation as the first presentation of tuberculosis: a case series. J Clin Diagn Res. 2016;10:NR01–3.

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Agrawal R, Gunasekeran DV, Raje D, Agarwal A, Nguyen QD, Kon OM, et al. For the Collaborative Ocular Tuberculosis Study Group; Global variations and challenges with tubercular uveitis in the collaborative ocular tuberculosis study. Investig Ophthalmol Vis Sci. 2018;59:4162–71.

    Article  Google Scholar 

  7. Betzler BK, Gupta V, Agrawal R. Clinics of ocular tuberculosis: a review. Clin Exp Ophthalmol. 2021;49:146–60.

    Article  PubMed  Google Scholar 

  8. Gupta A, Sharma A, Bansal R, Sharma K. Classification of intra-ocular tuberculosis. Ocul Immunol Inflamm. 2015;23:7–13.

    Article  PubMed  Google Scholar 

  9. Lou SM, Montgomery PA, Larkin KL, Winthrop K, Zierhut M, Rosenbaum JT, et al. Diagnosis and treatment for ocular tuberculosis among uveitis specialists: the international perspective. Ocul Immunol Inflamm. 2015;23:32–9.

    Article  PubMed  Google Scholar 

  10. Lou SM, Larkin KL, Winthrop K, Rosenbaum JT, Uveitis Specialists Study Group. Lack of consensus in the diagnosis and treatment for ocular tuberculosis among uveitis specialists. Ocul Immunol Inflamm. 2015;23:25–31.

    Article  CAS  PubMed  Google Scholar 

  11. Gupta V, Gupta A, Rao NA. Intraocular tuberculosis—an update. Surv Ophthalmol. 2007;52:561–87.

    Article  PubMed  Google Scholar 

  12. Agrawal R, Gupta B, Gonzalez-Lopez JJ, Rahman F, Phatak S, Triantafyllopoulou I, et al. The role of anti-tubercular therapy in patients with presumed ocular tuberculosis. Ocul Immunol Inflamm. 2015;23:40–6.

    Article  CAS  PubMed  Google Scholar 

  13. Pefkianaki M, Westcott M, Liew G, Lee R, Pavesio C, et al. Diagnostic and therapeutic challenges. Retina. 2014;34:1247–52.

    Article  PubMed  Google Scholar 

  14. Agrawal R, Gunasekeran DV, Gonzalez-Lopez JJ, Cardoso J, Gupta B, Addison PKF, et al. Peripheral retinal vasculitis: analysis of 110 consecutive cases and a contemporary reappraisal of tubercular etiology. Retina. 2017;37:112–7.

    Article  PubMed  Google Scholar 

  15. Gupta V, Shoughy SS, Mahajan S, Khairallah M, Rosenbaum JT, Curi A, et al. Clinics of ocular tuberculosis. Ocul Immunol Inflamm. 2015;23:14–24.

    Article  PubMed  Google Scholar 

  16. Gupta A, Bansal R, Gupta V, Sharma A, Bambery P. Ocular signs predictive of tubercular uveitis. Am J Ophthalmol. 2010;149:562–70.

    Article  PubMed  Google Scholar 

  17. Ang M, Vasconcelos-Santos DV, Sharma K, Accorniti M, Sharma A, Gupta A, et al. Diagnosis of ocular tuberculosis. Ocul Immunol Inflamm. 2018;26:208–16.

    Article  PubMed  Google Scholar 

  18. Knecht PB, Papadia M, Herbort CP. Secondary choriocapillaritis in infectious chorioretinitis. Acta Ophthalmol. 2013;91:e550–5.

    Article  PubMed  Google Scholar 

  19. Agrawal R, Gunasekeran DV, Grant R, Agarwal A, Kon OM, Nguyen Q, et al. Clinical features and outcomes of patients with tubercular uveitis treated with antitubercular therapy in the Collaborative Ocular Tuberculosis Study (COTS)-1. JAMA Ophthalmol. 2017;135:1318–27.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Dinnes J, Deeks J, Kunst H, Gibson A, Cummins E, Waugh N, et al. A systematic review of rapid diagnostic tests for the detection of tuberculosis infection. Health Technol Assess. 2007;11:1–196.

    Article  CAS  PubMed  Google Scholar 

  21. Centers for Disease Control and Prevention. Updated guidelines for using interferon gamma release assays to detect mycobacterium tuberculosis infection—United States, 2010. MMWR Morb Mortal Wkly Rep. 2010;59:1–25.

    Google Scholar 

  22. Wang L, Turner MO, Elwood RK, Schulzer M, FitzGerald JM. A meta-analysis of the effect of Bacille Calmette Guérin vaccination on tuberculin skin test measurements. Thorax. 2002;57:804–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Centers for Disease Control and Prevention. Nationwide shortage of tuberculin skin test antigens: CDC recommendations for patient care and public health practice. MMWR Morb Mortal Wkly Rep. 2019;68:552–3.

    Article  Google Scholar 

  24. Metcalfe JZ, Everett CK, Steingart KR, Cattamanchi A, Huang L, Hopewell PC, et al. Interferon-γ release assays for active pulmonary tuberculosis diagnosis in adults in low- and middle-income countries: systematic review and meta-analysis. J Infect Dis. 2011;204 Suppl 4:S1120–9.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Albini TA, Karakousis PC, Rao NA. Interferon-gamma release assays in the diagnosis of tuberculous uveitis. Am J Ophthalmol. 2008;146:486–8.

    Article  CAS  PubMed  Google Scholar 

  26. Kurup SK, Buggage RR, Clarke GL, Ursea R, Lim WK, Nussenblatt RB, et al. Gamma interferon assay as an alternative to PPD skin testing in selected patients with granulomatous intraocular inflammatory disease. Can J Ophthalmol. 2006;41:737–40.

    Article  PubMed  Google Scholar 

  27. Vasconcelos-Santos DV, Zierhut M, Rao NA. Strengths and weaknesses of diagnostic tools for tuberculous uveitis. Ocul Immunol Inflamm. 2009;17:351–5.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Jeong YJ, Lee KS. Pulmonary tuberculosis: up-to-date imaging and management. AJR Am J Roentgenol. 2008;191:834–44.

    Article  PubMed  Google Scholar 

  29. Sugita S, Ogawa M, Shimizu N, Morio T, Ohguro N, Nakai K, et al. Use of a comprehensive polymerase chain reaction system for diagnosis of ocular infectious diseases. Ophthalmology. 2013;120:1761–8.

    Article  PubMed  Google Scholar 

  30. Rosenbaum JT. To be or not TB? Br J Ophthalmol. 2014;98:999e1000.

    Article  Google Scholar 

  31. Agarwal A, Agrawal R, Gunasekaran DV, Raje D, Gupta B, Agrawal K, et al. The Collaborative Ocular Tuberculosis Study (COTS)-1 Report 3: polymerase chain reaction in the diagnosis and management of tubercular uveitis: global trends. Ocul Immunol Inflamm. 2017;27:465–73.

    Article  PubMed  Google Scholar 

  32. Gunasekeran DV, Agrawal R, Agarwal A, Carreno E, Raje D, Aggarwal K, et al. The Collaborative Ocular Tuberculosis Study (COTS)-1: a multinational review of 251 patients with tubercular retinal vasculitis. Retina. 2019;39:1623–30.

    Article  PubMed  Google Scholar 

  33. Agrawal R, Gunasekeran DV, Agarwal A, Carreno E, Aggarwal K, Gupta B, et al. The Collaborative Ocular Tuberculosis Study (COTS)-1: a multinational description of the spectrum of choroidal involvement in 245 patients with tubercular uveitis. Ocul Immunol Inflamm. 2018;29:1–11.

    Google Scholar 

  34. Agrawal R, Testi I, Mahajan S, Yuen YS, Agarwal A, Rousselot A, et al. The Collaborative Ocular Tuberculosis Study (COTS) Consensus (CON) Group Meeting Proceedings. Ocul Immunol Inflamm. 2020. https://doi.org/10.1080/09273948.2020.171602.

  35. Jones J, Hunter D. Consensus methods for medical and health services research. BMJ. 1995;311:376–80. https://doi.org/10.1136/bmj.311.7001.376.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. McMillan SS, King M, Tully MP. How to use the nominal group and Delphi techniques. Int J Clin Pharm. 2016;38:655–62. https://doi.org/10.1007/s11096-016-0257-x.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Agrawal R, Testi I, Mahajan S, Yuen YS, Agarwal A, Kon OM, et al. Collaborative Ocular Tuberculosis Study consensus guidelines on the management of tubercular uveitis report 1: guidelines for initiating anti- tubercular therapy in tubercular choroiditis. Ophthalmology. 2021;128:266–76.

  38. Agrawal R, Testi I, Bodaghi B, Barisani-Asenbauer T, Mccluskey P, Agarwal A, et al. Collaborative Ocular Tuberculosis Study Consensus Guidelines on the Management of Tubercular Uveitis Report 2: Guidelines for Initiating Antitubercular Therapy in Anterior Uveitis, Intermediate Uveitis, Panuveitis, and Retinal Vasculitis. Ophthalmology. 2021;128:277–87.

    Article  PubMed  Google Scholar 

  39. Derrick B, White P. Comparing two samples from an individual Likert question. Int J Math Stat. 2017;18:1–13.

    Google Scholar 

  40. Armstrong R. The midpoint on a five-point Likert-type scale. Percept Mot Skills. 1987;64:359–62. https://doi.org/10.2466/pms.1987.64.2.359.

    Article  Google Scholar 

  41. The Standardization of Uveitis Nomenclature (SUN) Working Group. Classification criteria for sarcoidosis-associated uveitis. Am J Ophthalmol. 2021;228:142–51.

    Article  Google Scholar 

  42. Collaborative Ocular Tuberculosis Study (COTS) Group. Standardization of Nomenclature for Ocular Tuberculosis—Results of Collaborative Ocular Tuberculosis Study (COTS) Workshop. Ocul Immunol Inflamm. 2019. https://doi.org/10.1080/09273948.2019.1653933.

  43. Apgar V. A Proposal for a New Method of Evaluation of the Newborn Infant. Originally published in July 1953, volume 32, pages 250–259. Anesth Analg. 2015;120:1056–9.

  44. Ibrahim LF, Hopper SM, Donath S, Salvin B, Babl FE, Bryant PA. Development and validation of a cellulitis risk score: the Melbourne ASSET score. Pediatrics. 2019;143:e20181420.

    Article  PubMed  Google Scholar 

  45. Ang M, Chee SP. Controversies in ocular tuberculosis. Br J Ophthalmol. 2017;101:6e9.

    Article  Google Scholar 

  46. Gupta V, Gupta A, Rao NA. Intraocular tuberculosis—an update. Surv Ophthalmol. 2007;52:561e587.

    Article  Google Scholar 

Download references

Acknowledgements

All authors contributed to the intellectual development of this paper. RA and VG conceived and planned the study. ZL wrote the first draft of the paper. ZL and RA performed the literature review. RA, ZL, BB, IT, SM, AR, JHK, JRS, PM, QDN, CP and VG contributed to interpreting the results and provided critical feedback to the paper. The final version of the paper has been seen and approved by all authors.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Rupesh Agrawal or Vishali Gupta.

Ethics declarations

Competing interests

RA, ZL, BB, IT, SM, AR, JHK, JRS, PM, QDN, CP and VG report no competing interests, financial or propriety, in the subject matter or materials discussed in this paper. JHK is a consultant for Gilead Pharma, a company evaluating a treatment for non-infectious uveitis, and equity owner for Betaliq, a company developing an intraocular pressure-lowering treatment. RA is supported by a grant from the National Medical Research Council (NMRC) by Ministry of Health, Singapore, for the Clinician Scientist Award (CSA) from 2020 to 2023. He has not received funding for his work in this publication.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Agrawal, R., Ludi, Z., Betzler, B.K. et al. The Collaborative Ocular Tuberculosis Study (COTS) calculator—a consensus-based decision tool for initiating antitubercular therapy in ocular tuberculosis. Eye 37, 1416–1423 (2023). https://doi.org/10.1038/s41433-022-02147-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41433-022-02147-7

This article is cited by

Search

Quick links