Modelling the late effects of cancer treatment on the ovary

University of St Andrews School of Computer Science

Modelling the late effects of cancer treatment on the ovary

Edinburgh Fertility 2016 Tom Kelsey

Overview

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•  Models of the healthy •  Equa/ons popula/on •  Sta/s/cs –  non-‐growing follicles –  ovarian volume

•  Model valida/on •  Use of the models to predict/quan/fy/ es/mate late effects School of Computer Science

–  p-‐values –  Correla/on coefficients –  Confidence intervals

•  Deriva/on details •  Funding logos •  Photos of colleagues Tom Kelsey -‐ Edinburgh Fer/lity 20th June 2016

Non-Growing Follicles

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•  Ovarian reserve –  Born with a population that declines until menopause –  NGFs are selected for maturation

•  Impossible to measure in vivo –  Using current technologies

•  Populations are counted in vitro –  Typically histological examination of stained tissue

School of Computer Science

Tom Kelsey -‐ Edinburgh Fer/lity 20th June 2016

NGFs – Wallace & Kelsey 2010

Wallace WH, Kelsey TW. Human ovarian reserve from concep/on to the menopause. PLoS ONE. 2010;5(1):e8772. School of Computer Science

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NGFs – Wallace & Kelsey 2010


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Ovarian Volume

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•  Indirect measure of ovarian reserve •  Possible to measure in vivo –  2D & 3D ultrasound

•  The assumption is that a large ovary contains more NGFs than a small one –  Clearly true when comparing pre- and postmenopausal ovaries –  We have no evidence for this assumption for pre-menopausal ages



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Kelsey TW, Dodwell SK, et al. Ovarian volume throughout life: a validated norma/ve model. Tom Kelsey -‐ Edinburgh Fer/lity PLoS ONE. 2013;8(9):e71465 School of Computer Science

20th June 2016

Model Validation

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•  We internally validate models before submission for review –  Careful checks that the best model isn’t based on a chance configura/on of the data

•  Ideally, we want external valida-on –  Comparison of our predic/ons to observa/ons made at a later date ... –  ... and in another lab

•  If observa/ons are close to predic/ons, the predic/ve model is a useful guide to normal values & ranges –  if not, it’s back to the drawing board School of Computer Science


Depmann M, Faddy MJ, et al. The rela/on between varia/on in size of the primordial follicle pool and age at natural menopause J Clin Endocrinol Metab 2015;100(6)

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Predicted in 2010

Observed in 2015



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McLaughlin M, Kelsey TW, et al. An externally validated age-‐related model of mean follicle density in the cortex of the human Tom Kelsey -‐ Edinburgh Fer/lity 20th June 2016 ovary. J Assist Rep Gen. 2015;32(7):1089-‐95. School of Computer Science

Using the models to assess infertility 11 •  We have external valida/on, and a con/nuous endeavor to improve models as new data become available –  Also jus/fying/tes/ng the inherent assump/ons

•  We now take the models as a base-‐line –  Represen/ng the popula/on aher zero-‐dose

•  If we know age at POI aher known doses ... •  ... And/or if we know MFD aher treatment •  We can es/mate the damage done to the ovarian reserve by the treatment Tom Kelsey -‐ Edinburgh Fer/lity

20th June 2016

Using the models to assess infertility 12

Tom Kelsey -‐ Edinburgh Fer/lity

20th June 2016

Predicting POI after radiotherapy

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Anderson RA, Mitchell RT, Kelsey TW, Spears N, Telfer EE, Wallace WH. Cancer treatment and gonadal func/on: experimental and established strategies for fer/lity preserva/on in children and young adults. Tom Kelsey -‐ Edinburgh Fer/lity 20th June 2016 Lancet Diabetes Endocrinol. 2015;3(7):556-‐67.

Effective Sterilising Doses

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Anderson RA, Mitchell RT, Kelsey TW, Spears N, Telfer EE, Wallace WHB. Cancer treatment and gonadal func/on: experimental and established strategies for fer/lity preserva/on in children and young adults. Lancet Diabetes Endocrinol. 2015;3(7):556-‐67. Tom Kelsey -‐ Edinburgh Fer/lity 20th June 2016

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McLaughlin M, Kelsey TW, Wallace WHB, Anderson RA, Telfer EE. Non-‐growing follicle density is increased following ABVD chemotherapy in the adult human ovary. Tom Kelsey -‐ Edinburgh Fer/lity 20th June 2016 Data not published

Summary

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•  NGFs and ovarian volumes introduced here

–  Other models have been derived, validated & published –  Uterine volume1, inhibin B (males)2, testosterone (males)3, AMH, ... –  Other applica/ons have been published –  PCOS, breast cancer4, IVF, diabetes5, ...

•  Each is a mul/-‐disciplinary effort to iden/fy, collect & analyse data –  Our own, and data published by others

•  Followed by model deriva/on, selec/on & (levels of) valida/on •  Our aim is useful and accurate quan/fica/on of the effects of treatment(s) on the fer/lity of survivors of cancer School of Computer Science


References

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1.  Kelsey, T. W., Ginbey, E., et al. (2016). A Validated Norma/ve Model for Human Uterine Volume from Birth to Age 40 Years. PloS one, 6, e0157375. 2.  Kelsey, T. W., Miles, A., et al. (2016). A Norma/ve Model of Serum Inhibin B in Young Males. PloS one, 4, e0153843. 3.  Kelsey, T. W., Li, L. Q., et al. (2014). A validated age-‐ related norma/ve model for male total testosterone shows increasing variance but no decline aher age 40 years. PloS one, 10, e109346. 4.  Phillips, K. A., Collins, I. M., et al. (2016). An/-‐Mullerian hormone serum concentra/ons of women with germline BRCA1 or BRCA2 muta/ons. Human reproduc:on, 5, 1126–1132. 5.  Iliodromi/, S., Sassarini, J., et al. (2016). Accuracy of circula/ng adiponec/n for predic/ng gesta/onal diabetes: a systema/c review and meta-‐analysis. Diabetologia, 4, 692–699. School of Computer Science


Thank You

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Any ques/ons?

