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Althaus, CL

Hay, P

Heijne, JCM

Herzog, SA

Kerry, S

Low, N

Oakeshott, P

BMC Infectious Diseases

English

PubMed

Abstract Background Pelvic inflammatory disease (PID) results from the ascending spread of microorganisms from the vagina and endocervix to the upper genital tract. PID can lead to infertility, ectopic pregnancy and chronic pelvic pain. The timing of development of PID after the sexually transmitted bacterial infection Chlamydia trachomatis (chlamydia) might affect the impact of screening interventions, but is currently unknown. This study investigates three hypothetical processes for the timing of progression: at the start, at the end, or throughout the duration of chlamydia infection. Methods We develop a compartmental model that describes the trial structure of a published randomised controlled trial (RCT) and allows each of the three processes to be examined using the same model structure. The RCT estimated the effect of a single chlamydia screening test on the cumulative incidence of PID up to one year later. The fraction of chlamydia infected women who progress to PID is obtained for each hypothetical process by the maximum likelihood method using the results of the RCT. Results The predicted cumulative incidence of PID cases from all causes after one year depends on the fraction of chlamydia infected women that progresses to PID and on the type of progression. Progression at a constant rate from a chlamydia infection to PID or at the end of the infection was compatible with the findings of the RCT. The corresponding estimated fraction of chlamydia infected women that develops PID is 10% (95% confidence interval 7-13%) in both processes. Conclusions The findings of this study suggest that clinical PID can occur throughout the course of a chlamydia infection, which will leave a window of opportunity for screening to prevent PID.</p

Herzog Sereina A

Althaus Christian L

Heijne Janneke CM

Oakeshott Pippa

Kerry Sally

Hay Phillip

Low Nicola

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Timing of progression from <it>Chlamydia trachomatis</it> infection to pelvic inflammatory disease: a mathematical modelling study

Queen Mary Research Online

2Division of Population Health Sciences and Education, St George’s, University of London, London

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Community-based trial of screening for Chlamydia trachomatis to prevent pelvic inflammatory disease: the POPI (prevention of pelvic infection) trial. Trials

Core Team: R: A Language and Environment for Statistical.

Describing progression form Chlamydia trachomatis and Neisseria gonorrhoeae infections to pelvic inflammatory disease: systematic review of mathematical modelling studies. Sex Transm Dis

Disease Control and Prevention: Case definitions for infectious conditions under public health surveillance. Centers for Disease Control and Prevention. MMWR Recomm Rep

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Timing of progression from Chlamydia trachomatis infection to pelvic inflammatory disease: a mathematical modelling study

Sereina A Herzog

Christian L Althaus

Janneke CM Heijne

Pippa Oakeshott

Sally Kerry

Phillip Hay

Nicola Low

Crossref

Timing of progression from Chlamydia trachomatisinfection to pelvic inflammatory disease: a mathematical modelling study

BACKGROUND: Pelvic inflammatory disease (PID) results from the ascending spread of microorganisms from the vagina and endocervix to the upper genital tract. PID can lead to infertility, ectopic pregnancy and chronic pelvic pain. The timing of development of PID after the sexually transmitted bacterial infection Chlamydia trachomatis (chlamydia) might affect the impact of screening interventions, but is currently unknown. This study investigates three hypothetical processes for the timing of progression: at the start, at the end, or throughout the duration of chlamydia infection. 



METHODS: We develop a compartmental model that describes the trial structure of a published randomised controlled trial (RCT) and allows each of the three processes to be examined using the same model structure. The RCT estimated the effect of a single chlamydia screening test on the cumulative incidence of PID up to one year later. The fraction of chlamydia infected women who progress to PID is obtained for each hypothetical process by the maximum likelihood method using the results of the RCT.



RESULTS: The predicted cumulative incidence of PID cases from all causes after one year depends on the fraction of chlamydia infected women that progresses to PID and on the type of progression. Progression at a constant rate from a chlamydia infection to PID or at the end of the infection was compatible with the findings of the RCT. The corresponding estimated fraction of chlamydia infected women that develops PID is 10% (95% confidence interval 7-13%) in both processes.



CONCLUSIONS: The findings of this study suggest that clinical PID can occur throughout the course of a chlamydia infection, which will leave a window of opportunity for screening to prevent PID

Heijne, JC

St George's Online Research Archive

1 Timing of Progression of Chlamydia trachomatis Infection to Pelvic Inflammatory Disease: A Mathematical Modelling Study  Sereina A. Herzog, Christian L. Althaus, Janneke C.M. Heijne, Pippa Oakeshott, Sally Kerry, Phillip Hay, Nicola Low  Additional File 1  Content 1.  Initial conditions and cumulative incidence of pelvic inflammatory disease (PID) ............................................. 2 2.  Maximum likelihood estimation of the fraction f of chlamydia infections progressing to PID (fMLE) ................. 3 3.  Akaike’s information criterion (AIC) ................................................................................................................... 3 4.  How incidence of PID accumulates in each type of progression ......................................................................... 3 5.  Result of multivariable sensitivity analysis .......................................................................................................... 5 6.  Varying mean time between start of infection and time point when progression to PID becomes possible ........ 6 7.  Appendix references ............................................................................................................................................. 7    2 1. Initial conditions and cumulative incidence of pelvic inflammatory disease (PID) The function for the cumulative incidence of PID cases C(t) at time point t depends for each type of progression (immediate progression, constant progression, progression at the end) on the specific incidence of PID cases and fulfils that C(0)=0. ܥ௜௠௠௘ௗ௜௔௧௘ሺݐሻ ൌ ݂ߣනܵሺ߬ሻ݀߬௧଴ൌ ݂ߣߙ ൅ ݎ ൅ ߣ ቈሺߙ ൅ ݎሻሺݏଵ ൅ ݏଶሻݐ ൅݁ିሺఈା௥ାఒሻ௧ሺሺߙ ൅ ݎሻݏଶ െ ߣݏଵሻߙ ൅ ݎ ൅ ߣ ቉െ ݂ߣሺሺߙ ൅ ݎሻݏଶ െ ߣݏଵሻሺߙ ൅ ݎ ൅ ߣሻଶ  ܥ௖௢௡௦௧௔௡௧ሺݐሻ ൌ ߛන ܫଵሺ߬ሻ݀߬	௧଴ൌ ߛ ቈߣሺݎ ൅ ߙሻሺݏଵ ൅ ݏଶ ൅ ݏଷሻሺߙ ൅ ݎ ൅ ߛሻሺߙ ൅ ݎ ൅ ߣሻ ݐ െ݁ିሺఈା௥ାఒሻ௧ߣ൫ሺߙ ൅ ݎሻሺݏଶ ൅ ݏଷሻ െ ߣݏଵ൯ሺߙ ൅ ݎ ൅ ߣሻଶሺߣ െ ߛሻ൅ ݁ିሺఈା௥ାఊሻ௧ሺݏଶሺߙ ൅ ݎ ൅ ߛሻߛ ൅ ݏଷሺݎ ൅ ߙሻߣ െ ߛߣሺݏଵ ൅ ݏଶሻሻሺߙ ൅ ݎ ൅ ߛሻଶሺߣ െ ߛሻ ቉െ ߛߣ െ ߛ ቈሺݏଶሺߙ ൅ ݎ ൅ ߛሻߛ ൅ ݏଷሺݎ ൅ ߙሻߣ െ ߛߣሺݏଵ ൅ ݏଶሻሻሺߙ ൅ ݎ ൅ ߛሻଶെ ߣ൫ሺߙ ൅ ݎሻሺݏଶ ൅ ݏଷሻ െ ߣݏଵ൯ሺߙ ൅ ݎ ൅ ߣሻଶ ቉ ܥ௘௡ௗሺݐሻ ൌ ݂ݎන ܫሺ߬ሻ݀߬௧଴ൌ ݂ݎߙ ൅ ݎ ൅ ߣ ቈߣሺݏଵ ൅ ݏଶሻݐ ൅݁ିሺఈା௥ାఒሻ௧൫ሺߙ ൅ ݎሻݏଶ െ ߣݏଵ൯ߙ ൅ ݎ ൅ ߣ ቉ െ݂ݎ൫ሺߙ ൅ ݎሻݏଶ െ ߣݏଵ൯ሺߙ ൅ ݎ ൅ ߣሻଶ   where s1=S(0), s2=I1(0) and s3=I2(0) describe the initial conditions for the constant progression scenario. The intervention group was treated for chlamydia infections and therefore has ݏଵ ൌ 1 െ ݌ ∗ ߜ, ݏଶ ൌ ݌ ∗ ߜ ௥௥ାఊ, ݏଷ ൌ ݌ ∗ ߜ ఊ௥ାఊ . The control group starts at steady state in the absence of the trial (α=0) with ݏଵ ൌ 1 െ ݌, ݏଶ ൌ ݌ ௥௥ାఊ and ݏଷ ൌ ݌ఊ௥ାఊ. The initial conditions for immediate progression and progression at the end of infection (where ߛ ൌ 0 and ܫሺݐሻ ൌ ܫଵሺݐሻ ൅ ܫଶሺݐሻ) are described as S(0)ൌ ݏଵ and ܫሺ0ሻ ൌ ݏଶ ൅ ݏଷ.   3 2. Maximum likelihood estimation of the fraction f of chlamydia infections progressing to PID (fMLE) The maximum likelihood estimate [1] of the fraction f of infected women who progress from chlamydia to PID is obtained by maximising the following likelihood L. We used subscript I in the likelihood to indicate the intervention group and subscript C for the control group. We assumed for both groups that the observed PID cases (oI, oC) are binomially distributed and that they are a mixture of cases caused by chlamydia and by other microorganisms. The probability for each woman to develop PID within the timeframe of one year is set to equal the overall cumulative incidence of PID cases after one year (eI, eC).  ܮ ൌ ෑ ൬ ௝ܰ݋௝ ൰ ௝݁௢ೕሺ1 െ ௝݁ሻேೕି௢ೕ௝∈ሼூ,஼ሽ  where Nj equals the number of women in each group. The derivations of eI and eC are explained in the method section of the main text. 3. Akaike’s information criterion (AIC) The Akaike’s information criterion (AIC) is defined as   ܣܫܥ ൌ െ2 logሺܮሻ ൅ 2݇  where L is the likelihood and k the number of estimated parameters in the model, k=1 for the model used in this study [2]. 4. How incidence of PID accumulates in each type of progression To illustrate how incidence of PID accumulates from the start of infection, a hypothetical cohort of women who became infected at the same time is followed over time. In this hypothetical cohort, women can develop PID according to the three processes described in the main text. Figure A1 shows the cumulative incidence of PID as a function of time since infection, using baseline values (see Table 1 in main text) and the maximum likelihood estimates (MLE) for the fraction progressing to PID ( ெ݂௅ா). We obtained the time point where half of the expected PID cases ( ெ݂௅ா/2) have occurred (T50 in Table A1) and indicated them with black dots in Figure A1.              In the immediate progression scenario, the time point when half of the expected PID cases occurred is 0 days. This is an intuitive consequence of the progression without a delay.   In the scenario with a constant daily risk of developing PID (constant progression) the cumulative incidence of PID is increasing fast in the beginning and flattens out (Figure A1). It takes 228 days until half of the expected PID cases are observed. In the progression at the end scenario, a similar behaviour for the cumulative incidence can be observed (Figure A1) and the half-value time (T50) is simply the half-life of infectious duration, i.e. 253 days (=ln(2)/r).  Table A1 Time until half of expected PID cases occured Type of progression ࢌࡹࡸࡱ* T50† Immediate progression 8.3 % 0 daysConstant progression 9.9 % 228 daysProgression at the end 10.0 % 253 days* MLE for fraction progressing to PID from Table 2. † Time point when half of the expected PID cases ( ெ݂௅ா/2) have occurred. PID, pelvic inflammatory disease; MLE, maximum likelihood estimate.  4 Figure A1 Illustration how incidence of PID accumulates in each type of progression. Cumulative incidence of PID following a hypothetical cohort of women who become infected at the same time, using baseline values and the maximum likelihood estimates for fraction progressing ( ெ݂௅ா): immediate progression (dashed line); constant progression (solid line); and progression at the end (dashed-dotted line). The black dots indicate when half of the expected PID cases occurred ( ெ݂௅ா/2). These values look similar because the duration until PID development is exponentially distributed in both scenarios but the definition of the duration until PID development becomes possible differs. In the progression at the end scenario, the duration until PID development equals the duration of the infection as PID develops just before natural clearance. In the constant progression, PID can develop throughout the infection which implies that some women will develop PID soon after infection whereas others will develop it very late in their infection.  Despite the similarities in the results about T50, the two scenarios differ conceptually regarding the window of opportunity for screening to prevent PID. In the progression at the end scenario the time window for preventing PID is the whole infection period whereas in the constant progression scenario the window might be shorter than the duration of infection.                                 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.00246810Immediate progressionConstant progressionProgression at the endTime since infection (years)Cumulative incidence of PID (%)5 Figure A2 The maximum likelihood estimations for the fraction f of progression for the sensitivity analysis with 1000 parameter sets: immediate progression (A); constant progression (B); and progression at the end (C). The mean and the median of the maximum likelihood estimations are listed within each panel and the 95% credibility interval (CI) is shown (dashed line).  ImmediateDensityFraction of chlamydia infected women who progress to PID (%)0 5 10 15 20 25 300.000.020.040.060.080.100.12AConstantDensityFraction of chlamydia infected women who progress to PID (%)0.000.020.040.060.080.100.12BAt endDensityFraction of chlamydia infected women who progress to PID (%)0.000.020.040.060.080.100.12CMean  8.4%Median  8.0%95% CI  3.0-15.8%Mean  9.7%Median  9.2%95% CI  3.3-18.5%Mean  9.8%Median  9.2%95% CI  3.3-18.8%0 5 10 15 20 25 300 5 10 15 20 25 305. Result of multivariable sensitivity analysis We did a multivariable sensitivity analysis by sampling each model parameter and the proportion of PID cases caused by chlamydia 1000 times from the distributions in Table 1 in the main text. The maximum likelihood estimates for the fraction of women progressing to PID (f) were determined and the quantiles (0.025 and 0.975) were obtained as 95% credibility interval, see Figure A2.                                       6 6. Varying mean time between start of infection and time point when progression to PID becomes possible For the sensitivity analysis we introduced a model framework which is similar to the constant progression scenario but allows varying the mean time between start of infection and the time point when progression to PID becomes possible. We used the same model structure as described in the main text with two stages of infections (I1, I2) but in doing so the interpretation of I2 has changed.   In stage I1 women are infected without having PID but those who make the transition to stage I2 with rate γ are now at risk to develop PID, i.e. upon entering I2 a fraction ሚ݂ will develop PID. Stage I2 is therefore a mixture of infected women with PID ( ሚ݂) and without PID (1- ሚ݂) and consequently incidence of chlamydial PID equals ሚ݂ߛܫଵ.  The introduction of the new parameter ሚ݂, fraction progressing to PID at transition to I2, is needed to specify the fraction of women who develop PID at the time point when PID becomes possible. This differs to the fraction ݂ in that ሚ݂ refers only to the women who remain infected at the time point at which progression to PID becomes possible. The interpretation of the fraction ݂ is the same as in the three types of progression of the main text, i.e. ݂ is the fraction of all women infected that will develop PID in the absence of an intervention The relationship between ݂ and ሚ݂ is  ݂ ൌ ሚ݂ ߛݎ ൅ ߛ  where ఊ௥ାఊ is the probability to make the transition from I1 to I2, r is the clearence rate of the infection, and 1/ߛ is the mean time between start of infection and the time point when progression to PID becomes possible. The relationship implies for a short mean duration until progression to PID becomes possible (i.e. small 1/ߛ) that ሚ݂ will be similar to ݂. But for increasing 1/ߛ follows that ሚ݂ has to increase too as women will have recovered without making the transition to I2. Note, there is a maximum value for the mean time 1/ߛ because the conditions ሚ݂ ൑ 100% and ݂ ൑ 100% have to be fulfilled.  The scenario of immediate progression can be approximated with 1/ߛ ൎ	0 which implies that ሚ݂ ൎ ݂; and the constant progression scenario corresponds to the situation with 	 ሚ݂=100%. The scenario with progression at the end of the infection cannot be approximated in this model framework.  We could not fit both unknown parameters (γ, ሚ݂) to the trial data as we have only two data points. We derived the maximum likelihood estimate (MLE) for the fraction of infected women developing PID at the transition to I2 ( ሚ݂) for different values for the mean duration (1/γ), using the observed cumulative incidences from the trial and the baseline values for all other paramters (see Table 1 in the main text). We varied the mean duration (1/γ) between 0 years and a maximum of 9.1 years, which is a consequence of the condition ሚ݂ ൑ 100%. For each mean duration value we obtained MLE of fraction ሚ݂, the corresponding MLE of fraction f (using the relationship stated above), and the AIC value. We also obtained the cumulative incidence of PID after one year for the intervention group and the control group.  The best fitting values for the fraction of all infected women developing PID ( ெ݂௅ா) are between 8.3% and 9.9% for varying the mean time between start of infection and the time point when progression to PID becomes possible (dashed line in panel A of Figure A3). Note, the estimates are in the same range as the three types of progression in the main text. The corresponding cumulative incidence of PID after one year are very similar for the intervention and control group if the mean time between start of infection and progression is short but diverge with increasing mean duration 7 (panel B). The AIC values are similar for the explored ranges of the mean duration (note the narrow scale of the y-axis in panel C), But the best fit model converges to the scenario when PID develops at a constant rate throughout the infection, i.e. ሚ݂ ൌ 100%.                                            7. Appendix references 1. Kirkwood BR, Sterne JAC: Essential medical statistics. Malden, Mass: Blackwell Science; 2003. 2. Burnham KP, Anderson DR: Model selection and multi-model inference: A practical information-theoretic approach. New York, NY: Springer; 2010. Figure A3 Varying mean time between start of infection and time point when progression to PID becomes possible (1/γ), using baseline values. Panel A, maximum likelihood estimators (MLE) for ሚ݂ெ௅ா respectively ெ݂௅ா; panel B, corresponding cumulative incidence of PID after one year for the MLE values for intervention group (solid line) and control group (dashed line); panel C, corresponding Akaike’s Information Criterion (AIC) values for the MLE values. In all panels, the black dot indicates the approximation of the immediate progression and the black quadrate corresponds to the scenario of constant progression. 0 1 2 3 4 5 6 7 8 9 100102030405060708090100At transition (fMLE)Overall (fMLE)~0 1 2 3 4 5 6 7 8 9 1012.012.112.212.312.412.512.612.712.812.913.013.113.213.313.413.50 1 2 3 4 5 6 7 8 9 100.00.51.01.52.0Mean time until progression to PID becomes possible (years)Cumulative incidence of PID after one year (%)BMean time until progression to PID becomes possible (years)Fraction of women progressing to PID (%)AMean time until progression to PID becomes possible (years)Akaike‘s Information CriterionCControl groupIntervention group

Timing of progression from Chlamydia trachomatis infection to pelvic inflammatory disease: a mathematical modelling study.

Springer - Publisher Connector

Background



Pelvic inflammatory disease (PID) results from the ascending spread of microorganisms from the vagina and endocervix to the upper genital tract. PID can lead to infertility, ectopic pregnancy and chronic pelvic pain. The timing of development of PID after the sexually transmitted bacterial infection Chlamydia trachomatis (chlamydia) might affect the impact of screening interventions, but is currently unknown. This study investigates three hypothetical processes for the timing of progression: at the start, at the end, or throughout the duration of chlamydia infection.

Methods



We develop a compartmental model that describes the trial structure of a published randomised controlled trial (RCT) and allows each of the three processes to be examined using the same model structure. The RCT estimated the effect of a single chlamydia screening test on the cumulative incidence of PID up to one year later. The fraction of chlamydia infected women who progress to PID is obtained for each hypothetical process by the maximum likelihood method using the results of the RCT.

Results



The predicted cumulative incidence of PID cases from all causes after one year depends on the fraction of chlamydia infected women that progresses to PID and on the type of progression. Progression at a constant rate from a chlamydia infection to PID or at the end of the infection was compatible with the findings of the RCT. The corresponding estimated fraction of chlamydia infected women that develops PID is 10% (95% confidence interval 7-13%) in both processes.

Conclusions



The findings of this study suggest that clinical PID can occur throughout the course of a chlamydia infection, which will leave a window of opportunity for screening to prevent PID

Herzog, Sereina A

Althaus, Christian L

Heijne, Janneke Cm

Oakeshott, Pippa

Kerry, Sally

Hay, Phillip

Low, Nicola

Bern Open Repository and Information System (BORIS)

http://doaj.org/search?source=%7B%22query%22%3A%7B%22bool%22%3A%7B%22must%22%3A%5B%7B%22term%22%3A%7B%22id%22%3A%223803652d66564d4a937bfb7701bed347%22%7D%7D%5D%7D%7D%7D

Timing of progression from Chlamydia trachomatis infection to pelvic inflammatory disease: a mathematical modelling study

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