Validation of a clinical prediction rule to predict asymptomatic chlamydia and gonorrhea infections among internet-based testers

Aidan Ablona; Titilola Falasinnu; Michael Irvine; Claudia Estcourt; Paul Flowers; Michelle Murti; Oralia Gómez-Ramírez; Christopher K. Fairley; Sharmistha Mishra; Ann Burchell; Troy Grennan; Mark Gilbert

doi:10.1097/OLQ.0000000000001340

Validation of a clinical prediction rule to predict asymptomatic chlamydia and gonorrhea infections among internet-based testers

Aidan Ablona, Titilola Falasinnu, Michael Irvine, Claudia Estcourt, Paul Flowers, Michelle Murti, Oralia Gómez-Ramírez, Christopher K. Fairley, Sharmistha Mishra, Ann Burchell, Troy Grennan, Mark Gilbert^*

^*Corresponding author for this work

Psychology

Research output: Contribution to journal › Article › peer-review

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Abstract

Background Clinical prediction rules (CPRs) can be used in sexually transmitted infection (STI) testing environments to prioritize individuals at the highest risk of infection and optimize resource allocation. We previously derived a CPR to predict asymptomatic chlamydia and/or gonorrhea (CT/NG) infection among women and heterosexual men at in-person STI clinics based on 5 predictors. Population differences between clinic-based and Internet-based testers may limit the tool's application across settings. The primary objective of this study was to assess the validity, sensitivity, and overall performance of this CPR within an Internet-based testing environment (GetCheckedOnline.com). Methods We analyzed GetCheckedOnline online risk assessment and laboratory data from October 2015 to June 2019. We compared the STI clinic population used for CPR derivation (data previously published) and the GetCheckedOnline validation population using χ2 tests. Calibration and discrimination were assessed using the Hosmer-Lemeshow goodness-of-fit test and the area under the receiver operating curve, respectively. Sensitivity and the fraction of total screening tests offered were quantified for CPR-predicted risk scores. Results Asymptomatic CT/NG infection prevalence in the GetCheckedOnline population (n = 5478) was higher than in the STI clinic population (n = 10,437; 2.4% vs. 1.8%, P = 0.007). When applied to GetCheckedOnline, the CPR had reasonable calibration (Hosmer-Lemeshow, P = 0.90) and discrimination (area under the receiver operating characteristic, 0.64). By screening only individuals with total risk scores ≥4, we would detect 97% of infections and reduce screening by 14%. Conclusions The application of an existing CPR to detect asymptomatic CT/NG infection is valid within an Internet-based STI testing environment. Clinical prediction rules applied online can reduce unnecessary STI testing and optimize resource allocation within publicly funded health systems.

Original language	English
Pages (from-to)	481-487
Number of pages	7
Journal	Sexually Transmitted Diseases
Volume	48
Issue number	7
DOIs	https://doi.org/10.1097/OLQ.0000000000001340
Publication status	Published - 1 Jul 2021

Funding

Conflict of Interest and Sources of Funding: This study was funded by the Canadian Institutes of Health Research (CIHR) Team Grant: HIV Implementation Science—Component 2 Grant (CTW-155387). A.A. and O.G.-R. report the aforementioned grants from the Canadian Institutes of Health Research, and O.G.-R. reports postdoctoral funding from the Canadian HIV Trials Network and postdoctoral funding from Michael Smith Foundation for Health Research during the conduct of the study.

Keywords

asymptomatic chlamydia
asymptomatic gonorrhea
clinical prediction rules (CPRs)
sexually transmitted infection (STI)
resource allocation
publicly funded health systems

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Ablona-etal-STD2021-Validation-clinical-prediction-rule-predict-asymptomatic-chlamydia-gonorrhea-infectionsFinal published version, 412 KBLicence: CC BY-NC-ND 4.0

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Ablona, A., Falasinnu, T., Irvine, M., Estcourt, C., Flowers, P., Murti, M., Gómez-Ramírez, O., Fairley, C. K., Mishra, S., Burchell, A., Grennan, T., & Gilbert, M. (2021). Validation of a clinical prediction rule to predict asymptomatic chlamydia and gonorrhea infections among internet-based testers. Sexually Transmitted Diseases, 48(7), 481-487. https://doi.org/10.1097/OLQ.0000000000001340

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abstract = "Background Clinical prediction rules (CPRs) can be used in sexually transmitted infection (STI) testing environments to prioritize individuals at the highest risk of infection and optimize resource allocation. We previously derived a CPR to predict asymptomatic chlamydia and/or gonorrhea (CT/NG) infection among women and heterosexual men at in-person STI clinics based on 5 predictors. Population differences between clinic-based and Internet-based testers may limit the tool's application across settings. The primary objective of this study was to assess the validity, sensitivity, and overall performance of this CPR within an Internet-based testing environment (GetCheckedOnline.com). Methods We analyzed GetCheckedOnline online risk assessment and laboratory data from October 2015 to June 2019. We compared the STI clinic population used for CPR derivation (data previously published) and the GetCheckedOnline validation population using χ2 tests. Calibration and discrimination were assessed using the Hosmer-Lemeshow goodness-of-fit test and the area under the receiver operating curve, respectively. Sensitivity and the fraction of total screening tests offered were quantified for CPR-predicted risk scores. Results Asymptomatic CT/NG infection prevalence in the GetCheckedOnline population (n = 5478) was higher than in the STI clinic population (n = 10,437; 2.4% vs. 1.8%, P = 0.007). When applied to GetCheckedOnline, the CPR had reasonable calibration (Hosmer-Lemeshow, P = 0.90) and discrimination (area under the receiver operating characteristic, 0.64). By screening only individuals with total risk scores ≥4, we would detect 97% of infections and reduce screening by 14%. Conclusions The application of an existing CPR to detect asymptomatic CT/NG infection is valid within an Internet-based STI testing environment. Clinical prediction rules applied online can reduce unnecessary STI testing and optimize resource allocation within publicly funded health systems.",

keywords = "asymptomatic chlamydia, asymptomatic gonorrhea, clinical prediction rules (CPRs), sexually transmitted infection (STI), resource allocation, publicly funded health systems",

author = "Aidan Ablona and Titilola Falasinnu and Michael Irvine and Claudia Estcourt and Paul Flowers and Michelle Murti and Oralia G{\'o}mez-Ram{\'i}rez and Fairley, {Christopher K.} and Sharmistha Mishra and Ann Burchell and Troy Grennan and Mark Gilbert",

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Ablona, A, Falasinnu, T, Irvine, M, Estcourt, C, Flowers, P, Murti, M, Gómez-Ramírez, O, Fairley, CK, Mishra, S, Burchell, A, Grennan, T & Gilbert, M 2021, 'Validation of a clinical prediction rule to predict asymptomatic chlamydia and gonorrhea infections among internet-based testers', Sexually Transmitted Diseases, vol. 48, no. 7, pp. 481-487. https://doi.org/10.1097/OLQ.0000000000001340

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T1 - Validation of a clinical prediction rule to predict asymptomatic chlamydia and gonorrhea infections among internet-based testers

AU - Ablona, Aidan

AU - Falasinnu, Titilola

AU - Irvine, Michael

AU - Estcourt, Claudia

AU - Flowers, Paul

AU - Murti, Michelle

AU - Gómez-Ramírez, Oralia

AU - Fairley, Christopher K.

AU - Mishra, Sharmistha

AU - Burchell, Ann

AU - Grennan, Troy

AU - Gilbert, Mark

PY - 2021/7/1

Y1 - 2021/7/1

N2 - Background Clinical prediction rules (CPRs) can be used in sexually transmitted infection (STI) testing environments to prioritize individuals at the highest risk of infection and optimize resource allocation. We previously derived a CPR to predict asymptomatic chlamydia and/or gonorrhea (CT/NG) infection among women and heterosexual men at in-person STI clinics based on 5 predictors. Population differences between clinic-based and Internet-based testers may limit the tool's application across settings. The primary objective of this study was to assess the validity, sensitivity, and overall performance of this CPR within an Internet-based testing environment (GetCheckedOnline.com). Methods We analyzed GetCheckedOnline online risk assessment and laboratory data from October 2015 to June 2019. We compared the STI clinic population used for CPR derivation (data previously published) and the GetCheckedOnline validation population using χ2 tests. Calibration and discrimination were assessed using the Hosmer-Lemeshow goodness-of-fit test and the area under the receiver operating curve, respectively. Sensitivity and the fraction of total screening tests offered were quantified for CPR-predicted risk scores. Results Asymptomatic CT/NG infection prevalence in the GetCheckedOnline population (n = 5478) was higher than in the STI clinic population (n = 10,437; 2.4% vs. 1.8%, P = 0.007). When applied to GetCheckedOnline, the CPR had reasonable calibration (Hosmer-Lemeshow, P = 0.90) and discrimination (area under the receiver operating characteristic, 0.64). By screening only individuals with total risk scores ≥4, we would detect 97% of infections and reduce screening by 14%. Conclusions The application of an existing CPR to detect asymptomatic CT/NG infection is valid within an Internet-based STI testing environment. Clinical prediction rules applied online can reduce unnecessary STI testing and optimize resource allocation within publicly funded health systems.

AB - Background Clinical prediction rules (CPRs) can be used in sexually transmitted infection (STI) testing environments to prioritize individuals at the highest risk of infection and optimize resource allocation. We previously derived a CPR to predict asymptomatic chlamydia and/or gonorrhea (CT/NG) infection among women and heterosexual men at in-person STI clinics based on 5 predictors. Population differences between clinic-based and Internet-based testers may limit the tool's application across settings. The primary objective of this study was to assess the validity, sensitivity, and overall performance of this CPR within an Internet-based testing environment (GetCheckedOnline.com). Methods We analyzed GetCheckedOnline online risk assessment and laboratory data from October 2015 to June 2019. We compared the STI clinic population used for CPR derivation (data previously published) and the GetCheckedOnline validation population using χ2 tests. Calibration and discrimination were assessed using the Hosmer-Lemeshow goodness-of-fit test and the area under the receiver operating curve, respectively. Sensitivity and the fraction of total screening tests offered were quantified for CPR-predicted risk scores. Results Asymptomatic CT/NG infection prevalence in the GetCheckedOnline population (n = 5478) was higher than in the STI clinic population (n = 10,437; 2.4% vs. 1.8%, P = 0.007). When applied to GetCheckedOnline, the CPR had reasonable calibration (Hosmer-Lemeshow, P = 0.90) and discrimination (area under the receiver operating characteristic, 0.64). By screening only individuals with total risk scores ≥4, we would detect 97% of infections and reduce screening by 14%. Conclusions The application of an existing CPR to detect asymptomatic CT/NG infection is valid within an Internet-based STI testing environment. Clinical prediction rules applied online can reduce unnecessary STI testing and optimize resource allocation within publicly funded health systems.

KW - asymptomatic chlamydia

KW - asymptomatic gonorrhea

KW - clinical prediction rules (CPRs)

KW - sexually transmitted infection (STI)

KW - resource allocation

KW - publicly funded health systems

U2 - 10.1097/OLQ.0000000000001340

DO - 10.1097/OLQ.0000000000001340

M3 - Article

C2 - 33315748

AN - SCOPUS:85108021008

SN - 0148-5717

VL - 48

SP - 481

EP - 487

JO - Sexually Transmitted Diseases

JF - Sexually Transmitted Diseases

IS - 7

ER -

Validation of a clinical prediction rule to predict asymptomatic chlamydia and gonorrhea infections among internet-based testers

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