Use of Prognostic Meteorological Model Output in Dispersion Models
Prognostic models in infertility
-
Upload
hesham-al-inany -
Category
Health & Medicine
-
view
627 -
download
0
description
Transcript of Prognostic models in infertility
![Page 2: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/2.jpg)
Basic fertility work up
referral gyn
HistoryPhysical examination
Cycle evaluation
Ovulation
Semen analysis
? PCT
Tubalpatency:
CATHSGDLS
FSH, E2AFC
![Page 3: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/3.jpg)
Causes of infertility
• Azoospermia• Anovulation• Double sided tubal occlusion• Sexual dysfunction
![Page 4: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/4.jpg)
Causes of subfertility
• Unexplained subfertility• One-sided tubal pathology• Cervical factor subfertility• Endometriosis• Decreased semen quality • Decreased intercourse frequency
![Page 5: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/5.jpg)
Evers JL, Lancet 2002
Infertility or subfertility?
![Page 6: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/6.jpg)
Clinical problem
• Distinction between couples who need treatment and couples who are likely to conceive spontaneously
![Page 7: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/7.jpg)
Clinical Problem II
• You scheduled a couple to do ICSI and the woman asked you : What is my chance to get a baby after doing ICSI???
![Page 8: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/8.jpg)
Gynaecologists differ widely in estimating pregnancy chances of subfertile couples
Van der Steeg et al.,HR, 2006
![Page 9: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/9.jpg)
Why Models!!
• Prediction models are intended to help gynaecologists in patient communication and decision making about treatment
![Page 10: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/10.jpg)
How to Choose: Expectant management or intervention
• Prediction models for Chance to concieve naturally (home conception) (treatment independent pregnancy)
• Prediction models for pregnancy after IVF• Prediction models for pregnancy after IUI
![Page 11: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/11.jpg)
EimersCollinsSnick HunaultFemale age+ + - +Duration subfertility+ + + +F.A. manUrethritis vg. man
+ -
- -
- -
--
prim/ sec subfertility+ + - +Anovulation- - + -Tubal pathology- + + -Semen-analysis + + - +Endometriosis- + --PCTReferral status
+ - + -/++
Hunault et al. HR 2004Hunault et al. HR 2004
Prediction models for spontaneous pregnancy
![Page 12: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/12.jpg)
Calculation Prognosis
P = 1-0,0166P = 1-0,0166EXP(-0,053*EXP(-0,053*ageage-0,152*-0,152*durationduration-0,447*-0,447*prim/secprim/sec+0.0035*+0.0035*prog.motprog.mot-0,949*-0,949*PCTPCT-0,321*-0,321*referralreferral))
![Page 13: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/13.jpg)
External validation
the agreement between predicted probabilities and the outcome event rates
CalibrationCalibration
![Page 14: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/14.jpg)
Calibration plot for unexplained subfertility
Synthesis model without PCT
Predicted probability
0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0
Obs
erve
d pr
obab
ility
0,0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1,0
10 groups of N~260
Calibration Synthesis model
Van der Steeg HR 2007
![Page 15: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/15.jpg)
http://http://www.amc.nl/prognosticmodelhttp://http://www.amc.nl/prognosticmodel
![Page 16: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/16.jpg)
Clinical consequences
• Couples with prognosis <30% = IVFCouples with prognosis <30% = IVF• Couples with prognosis > 40% = Couples with prognosis > 40% =
expectant management expectant management • Couples with prognosis 30-40% = IUICouples with prognosis 30-40% = IUI
![Page 17: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/17.jpg)
Expectant management or intervention
• Prediction models for Chance to concieve naturally (home conception) (treatment independent pregnancy)
• Prediction models for pregnancy after IVF• Prediction models for pregnancy after IUI
![Page 18: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/18.jpg)
Protocols for IVF GnRH AntagonistGnRH AntagonistProtocolsProtocols
GnRH GnRH AgonistAgonistProtocolsProtocols
225 IU per day225 IU per day(150 IU Europe)(150 IU Europe) Individualized Dosing of FSH/HMGIndividualized Dosing of FSH/HMG
250 250 g per day antagonistg per day antagonist
Individualized Dosing of FSH/HMGIndividualized Dosing of FSH/HMG
GnRHa 1.0 mg per day GnRHa 1.0 mg per day up to 21 daysup to 21 days 0.5 mg per day of GnRHa0.5 mg per day of GnRHa
225 IU per day225 IU per day(150 IU Europe)(150 IU Europe)
Day 6Day 6of FSH/HMGof FSH/HMG
DayDayof of hCGhCG
Day 1 Day 1 of FSH/HMGof FSH/HMG
Day 6Day 6of FSH/HMGof FSH/HMG
DayDayof hCGof hCG
7 – 8 days7 – 8 daysafter estimated ovulationafter estimated ovulation
Down regulationDown regulation
Day 2 or 3Day 2 or 3of mensesof menses
Day 1 Day 1 FSH/HMGFSH/HMG
![Page 19: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/19.jpg)
Which day!!!
• Day of start of cycle• Day of start of stimulation• Day of OPU• Day of ET• the time of embryo transfer will be more
accurate • but limited since the couple has already gone
through the whole process of IVF.
![Page 20: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/20.jpg)
Ideal model
• the probability of live birth in an IVF cycle prior to start of ovarian stimulation.
![Page 21: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/21.jpg)
Day of start: Baseline factors
• female age,• duration of infertility, • primary cause of infertility, • duration of GnRH agonist use, • Hormonal level• the number of previous IVF cycle
![Page 22: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/22.jpg)
• The age of the woman is still considered to be the most important predictor of IVF success (Broekmans and Klinkert, 2004).
![Page 23: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/23.jpg)
• increasing duration of infertility has also been shown to be negative impact , even after adjustment for age, whereas previous pregnancy increases the likelihood of success (Collins et al., 1995; Templeton et al,1996).
![Page 24: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/24.jpg)
• couples with different infertility diagnoses will likely have different probabilities of achieving a live birth
![Page 25: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/25.jpg)
Ovarian reserve tests
• Basal FSH, inhibin B, and anti-Müllerian hormone concentrations, as well as antral follicles count can be used to measure the
ovarian reserve (Broekmans et al., 2006; Kwee et al., 2008).
![Page 26: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/26.jpg)
AMH
• If kits are available, AMH measurement could be the most useful in the prediction of ovarian response in anovulatory women.
• It is done at any day of cycle• It is too expensive• Exact normal levels not yet well agreed upon
![Page 27: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/27.jpg)
?Pregnancy
• correlation with the degree of response to COH, but identifying poor responders by means of these tests has low prognostic value in relation to the chance of live birth after IVF
Broekmans et al. (2006)
![Page 28: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/28.jpg)
How to build a model!
• Multivariate logistic regression analysis for previous prognostic variables to create prediction models of ovarian response and/or ongoing pregnancy has been used to a lesser extent (e.g., Bancsi et al., 2002).
![Page 29: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/29.jpg)
Existing Models
• Most statistical models for prediction of IVF outcome use both prestimulation parameters and data obtained during the treatment, such as data on embryos
![Page 30: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/30.jpg)
IVF prediction modelsPrediction modelsOutcomeDiscriminationCalibration
Templeton (1996)IVF0.63good
![Page 31: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/31.jpg)
![Page 32: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/32.jpg)
Calculation • The predicted probability (P) of achieving a live birth
after IVF was calculated using the Templeton the model:
• Where y was defined as y = –2.028 + [0.00551x(age – 16)2] –
[0.00028x(age – 16)3] + [i – (0.0690x no. of unsuccessful IVF attempts)] – (0.0711xtubal subfertility) + (0.7587xlive birth after IVF) + (0.2986 x previous pregnancy after IVF which did not result in a live birth) +
(0.2277x live birth which was not a result of IVF) + (0.1117x previous pregnancy, not after IVF and which did not result in a live birth).
![Page 33: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/33.jpg)
IVF prediction modelsPrediction modelsOutcomeDiscriminationCalibration
Templeton (1996)IVF0.63good
![Page 34: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/34.jpg)
Lintsen, A.M.E. et al. Hum. Reprod. 2007
![Page 35: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/35.jpg)
• classified for each woman into one of three groups, i.e.,
• (i) predictor of good prognosis• (ii) intermediate prognosis • (iii) predictor of poor prognosis.
![Page 36: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/36.jpg)
Expectant management or intervention
• Prediction models for Chance to concieve naturally (home conception) (treatment independent pregnancy)
• Prediction models for pregnancy after IUI• Prediction models for pregnancy after IVF
![Page 37: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/37.jpg)
Prognostic factors of pregnancy in intrauterine insemination
• Women with intermediate prognosis
![Page 38: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/38.jpg)
IUI prediction modelprediction modelsOutcomeDiscriminationCalibration
Steures (2004)IUI0.59good
![Page 39: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/39.jpg)
39
PICO
Patientwoman, 34 years, 2ys 1ry unexplained inf.
InterventionIUI
Comparisonwait
OutcomePregnancy
![Page 40: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/40.jpg)
![Page 41: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/41.jpg)
![Page 42: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/42.jpg)
months to ongoing pregnancy363024181260
Cum
ulat
ive o
ngoi
ng p
regn
ancy
rate
1,0
0,8
0,6
0,4
0,2
0,0
IUI-censoredexp-censoredIUIexp
exp=1, IUI=2
-- delayed treatment-- early treatment
RR: 1,0 (CI: 0,86-1,2)
N= 90 (71%)N= 90 (71%)
![Page 43: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/43.jpg)
Take Home Message
• Prediction models are now available and ready for use
• Female age is the overwhelming factor affecting prediction models
• The prognosis should be discussed clearly with the patients based on scientific evidence and existing models.
![Page 44: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/44.jpg)
However
• Patient preferences• Private vs medical insurance• Patient values
![Page 45: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/45.jpg)
http://http://www.amc.nl/prognosticmodelhttp://http://www.amc.nl/prognosticmodel
![Page 46: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/46.jpg)
Clinical consequences
• Couples with prognosis <30% = IVFCouples with prognosis <30% = IVF• Couples with prognosis > 40% = Couples with prognosis > 40% =
expectant management expectant management • Couples with prognosis 30-40% = IUICouples with prognosis 30-40% = IUI
![Page 47: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/47.jpg)
Lintsen, A.M.E. et al. Hum. Reprod. 2007
![Page 48: Prognostic models in infertility](https://reader033.fdocuments.net/reader033/viewer/2022061103/53f80ace8d7f7216518b460e/html5/thumbnails/48.jpg)
THANK You