Date post: | 22-Aug-2014 |
Category: |
Health & Medicine |
Upload: | hesham-al-inany |
View: | 617 times |
Download: | 0 times |
Basic fertility work up
referral gyn
HistoryPhysical examination
Cycle evaluation
Ovulation
Semen analysis
? PCT
Tubalpatency:
CATHSGDLS
FSH, E2AFC
Causes of infertility
• Azoospermia• Anovulation• Double sided tubal occlusion• Sexual dysfunction
Causes of subfertility
• Unexplained subfertility• One-sided tubal pathology• Cervical factor subfertility• Endometriosis• Decreased semen quality • Decreased intercourse frequency
Evers JL, Lancet 2002
Infertility or subfertility?
Clinical problem
• Distinction between couples who need treatment and couples who are likely to conceive spontaneously
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???
Gynaecologists differ widely in estimating pregnancy chances of subfertile couples
Van der Steeg et al.,HR, 2006
Why Models!!
• Prediction models are intended to help gynaecologists in patient communication and decision making about treatment
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
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
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))
External validation
the agreement between predicted probabilities and the outcome event rates
CalibrationCalibration
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
http://http://www.amc.nl/prognosticmodelhttp://http://www.amc.nl/prognosticmodel
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
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
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
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.
Ideal model
• the probability of live birth in an IVF cycle prior to start of ovarian stimulation.
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
• The age of the woman is still considered to be the most important predictor of IVF success (Broekmans and Klinkert, 2004).
• 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).
• couples with different infertility diagnoses will likely have different probabilities of achieving a live birth
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).
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
?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)
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).
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
IVF prediction modelsPrediction modelsOutcomeDiscriminationCalibration
Templeton (1996)IVF0.63good
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).
IVF prediction modelsPrediction modelsOutcomeDiscriminationCalibration
Templeton (1996)IVF0.63good
Lintsen, A.M.E. et al. Hum. Reprod. 2007
• classified for each woman into one of three groups, i.e.,
• (i) predictor of good prognosis• (ii) intermediate prognosis • (iii) predictor of poor prognosis.
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
Prognostic factors of pregnancy in intrauterine insemination
• Women with intermediate prognosis
IUI prediction modelprediction modelsOutcomeDiscriminationCalibration
Steures (2004)IUI0.59good
39
PICO
Patientwoman, 34 years, 2ys 1ry unexplained inf.
InterventionIUI
Comparisonwait
OutcomePregnancy
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%)
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.
However
• Patient preferences• Private vs medical insurance• Patient values
http://http://www.amc.nl/prognosticmodelhttp://http://www.amc.nl/prognosticmodel
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
Lintsen, A.M.E. et al. Hum. Reprod. 2007
THANK You