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Despite a significant number of studies on female fertility following childhood, adolescent, and young adult (CAYA) cancer, studies establishing precise (dose-related) estimates of treatment-related risks are still scarce. Previous studies have been underpowered, did not include detailed treatment information, or were based on self-report only without any hormonal assessments. More precise assessments of who is at risk for sub- or infertility are needed.
The objective of our study is to describe the design and methods of 2 studies on female fertility (a cohort study and a nested case-control study) among female survivors of CAYA cancer performed within the European PanCareLIFE project.
For the cohort study, which aims to evaluate the overall risk of fertility impairment, as well as the risk for specific subgroups of female CAYA cancer survivors, 13 institutions from 9 countries provide data on fertility impairment. Survivors are defined as being fertility impaired if they meet at least one of 8 different criteria based on self-reported and hormonal data. For the nested case-control study, which aims to identify specific treatment-related risk factors associated with fertility impairment in addition to possible dose-response relationships, cases (fertility impaired survivors) are selected from the cohort study and matched to controls (survivors without fertility impairment) on a 1:2 basis.
Of the 10,964 survivors invited for the cohort study, data are available from 6619 survivors, either questionnaire-based only (n=4979), hormonal-based only (n=72), or both (n=1568). For the nested case-control study, a total of 450 cases and 882 controls are identified.
Results of both PanCareLIFE fertility studies will provide detailed insight into the risk of fertility impairment following CAYA cancer and diagnostic- or treatment-related factors associated with an increased risk. This will help clinicians to adequately counsel both girls and young women, who are about to start anticancer treatment, as well as adult female CAYA cancer survivors, concerning future parenthood and to timely refer them for fertility preservation. Ultimately, we aim to empower patients and survivors and improve their quality of life.
RR1-10.2196/10824
Advances in diagnosis and treatment of childhood cancer have led to major improvements in 10-year survival rate, which now exceeds 80% [
Despite a significant number of studies on female fertility following childhood and adolescent cancer, studies establishing precise (dose-related) estimates of treatment-related risks are scarce. Previous studies have been underpowered [
We, therefore, initiated the PanCareLIFE project. This pan-European project, originating from the PanCare network, is a European Union funded project (7th Framework Programme, Theme Health), coordinated by the University Medical Center Mainz (Germany), in which investigators from 10 countries provide data from over 15,000 CAYA cancer survivors [
The aim of the female fertility cohort study is to evaluate the overall prevalence of fertility impairment among female CAYA cancer survivors who are at least 5 years past diagnosis and alive at the time of study assessment. Moreover, it aims to assess the prevalence of fertility impairment for specific subgroups of female CAYA cancer survivors based on cancer diagnosis, type of treatment (simple, yes or no, information on chemotherapy, radiotherapy, and surgery), age at treatment, and calendar period of treatment.
In total, 13 institutions from 9 countries (Germany, Czech Republic, Netherlands, Italy, Switzerland, France, United Kingdom, Norway, and Israel) collect cross-sectional data for the PanCareLIFE female fertility cohort study. These institutions, referred to as data providers, provide data from 16 different institutional cohorts in total. Two of these cohorts are registry-based cohorts (VIVE cohort and the Swiss Childhood Cancer Survivor Study cohort), whereas all other cohorts are hospital-based. Some of these data providers have previously collected their data as part of a local fertility study [
The eligibility criteria for the female fertility cohort study as well as the different survivor groups identified based on eligibility and type of response are described in
Those who do not respond to the invitation as well as those who actively refuse to participate are categorized as nonparticipants. Participants are defined as those who agree to participate by providing either questionnaire data only, hormonal data only, or both. All local ethical committees have approved the use of the collected data from their institute for the PanCareLIFE project.
For all women in the base cohort demographic, diagnostic and treatment-related data are collected from medical record files and registries. Basic demographic data include month and year of birth and of latest follow-up. Diagnostic data include type of diagnosis (based on the 3rd version of the International Classification of Childhood Cancer) [
Data on fertility impairment are collected by questionnaire and hormonal assessments. A specific PanCareLIFE fertility questionnaire is developed for those data providers who collect questionnaire data on fertility issues during the PanCareLIFE project. This questionnaire evaluates sociodemographic and menstrual cycle characteristics, menopausal status, use of oral contraceptives and hormones, reproductive history, and smoking and alcohol behaviors. The questionnaire is translated from the original English into German, Czech, Italian, and Hebrew. All translated questionnaires are back-translated into English (by another translator) to check if the translation is performed properly.
Questionnaire data from questionnaires used by data providers for previous local fertility studies address fertility issues using different questions at different levels of detail and with different answer categories. Therefore, a specific task for WP3 investigators is to recode the relevant data from these questionnaires for compatibility with the variables used in the PanCareLIFE fertility questionnaire in close collaboration with the relevant data provider to make them as compatible as possible.
Hormonal measurements primarily involve the assessment of AMH levels. Study participants are asked to provide a blood sample during a clinic visit (which takes place either as part of standard follow-up care or is specifically scheduled for the study). Part of the sample is centrifuged and stored at −20°C. Subsequently, serum samples are transported in batches by courier to AUMC, where AMH levels are determined centrally in the endocrine laboratory. An ultrasensitive Elecsys AMH assay is used (Roche Diagnostics GmbH, Mannheim, Germany) with an intraassay coefficient of variation of 0.5%-1.8%, a limit of detection of 0.01 µg/L, and a limit of quantitation of 0.03 µg/L [
Data providers collect all data from their own survivor cohort, enter them into a local study database (under a unique PanCareLIFE-ID number), anonymize the data, check the quality of the data, and then send the data to the coordinating PanCareLIFE data center in Mainz. In this center, all subjects are assigned a new unique identification number. Subsequently, the data are compiled and sent to the WP3 investigators at AUMC, as seen in
Characteristics of cohorts included in the cohort study and the nested case-control study.
Data provider or institute | Study cohort | Data | Women invited (n=10,964) of total base cohorta (N=14,379), n/N | Questionnaires provided (N=6547), n | Serum samples provided (N=1640), n | Time period of data collection |
DCOG LATER (Amsterdam UMC, Erasmus Medical Center Rotterdam)b, Netherlands | DCOG LATER cohortc [ |
PRd | 1684/2190 | 1109 | 619 | 2004-2014 |
Netherlands Cancer Institute Amsterdam, Netherlands | Hodgkin Lymphoma cohort [ |
PR | 275/450 | 203 | 0 | 1997-2016 |
Universitätsklinikum Bonn, Germany | VIVE cohortc | PR | 4467/5909 | 2482 | 0 | 2014-2015 |
Westfaelische Wilhelms-Universitaet Muensterb, Germany | Ewing 2008 Clinical Trials cohort | DUe | 140/161 | 46 | 24 | 2015-2016 |
Charité - Universitätsmedizin Berlin, Germany | Berlin Hormone Analyses cohortc [ |
PR | 344/402 | 83 | 69 | 2008-2009 |
Fakultni nemocnice Brnob, Czech Republic | Cohort female 5-yr cancer survivors Brnoc | DU | 203/283 | 182 | 180 | 2015-2016 |
Fakultni nemocnice v Motolb, Czech Republic | Cohort female 5-yr cancer survivors Motolc | DU | 1063/1398 | 574 | 301 | 2014-2016 |
Istituto Giannina Gaslinib, Italy | Gaslini female survivors cohortc | DU | 814/1111 | 563 | 122 | 2015-2016 |
University of Bern, Switzerland | Swiss Childhood Cancer Survivor Study cohort 1c [ |
PR | 977/1135 | 685 | 0 | 2007-2013 |
University of Bern, Switzerland | Swiss Childhood Cancer Survivor Study cohort 2c [ |
PR | 228/335 | 113 | 0 | 2015-2016 |
Great Ormond Street Children’s Hospital/University College London Hospitalc, United Kingdom | Hematopoietic stem cell transplantation cohortc | DU | 93/95 | 50 | 44 | 2015-2016 |
Oslo University Hospitalb, Norway | Lymphoma survivor cohort [ |
PR | 82/Unknown | 51 | 46 | 2007-2009 |
Oslo University Hospitalb, Norway | Acute lymphoblastic leukaemia survivor cohort [ |
PR | 103/175 | 82 | 65 | 2009-2010 |
University hospital Saint-Étienneb, France | Rhone Alpe cohort 1c | PR | 120/212 | 120 | 35 | 2005-2013 |
University hospital Saint-Étienneb, France | Rhone Alpe cohort 2c | PR | 220/284 | 102 | 62 | 2015-2016 |
Edmond and Lily Safra Children's Hospital, Sheba Medical Centerb, Israel | The Edmond and Lily Safra Children's Hospital Late Effects cohortc | DU | 151/239 | 102 | 73 | 2015-2016 |
aBase cohort is the subjects fulfilling inclusion criteria of study.
bInstitutes participating in the nested case-control study.
cVarious cancer diagnoses.
dPR: data collected prior to PanCareLIFE project.
eDU: data collected during PanCareLIFE project.
Flow chart of eligible, invited, and participating subjects of the 2 fertility studies within the PanCareLIFE project.
The primary outcome of the cohort study is
Low AMH is defined as an AMH level <0.5 µg/L [
Criterion 1: Primary amenorrhea (never had menses) in combination with a high follicle stimulating hormone (FSH) and/or a low anti-Müllerian hormone (AMH) level.
Criterion 2: Secondary amenorrhea (no menses for >12 months before the age of 40) in combination with a high FSH and/or a low AMH level.
Criterion 3: High FSH level in combination with a low AMH level, while being <40 years of age at time of study assessment.
Criterion 4: Primary amenorrhea (without information on AMH or FSH level).
Criterion 5: Secondary amenorrhea (without information on AMH or FSH level).
Criterion 6: Low AMH level and <30 years of age at time of study assessment and not using exogenous reproductive hormones at time of blood sampling.
Criterion 7: Use of artificial reproductive techniques (excluding those who reported male factor as the single cause of subfertility) and being <40 years of age at time of study assessment.
Criterion 8: Tried to conceive for at least 12 consecutive months without success and being <40 years of age at time of study assessment.
The overall prevalence of fertility impairment will be defined as the number of participating survivors who are fertility impaired divided by the total number of participating survivors. The prevalence of fertility impairment will also be calculated for subgroups based on cancer diagnosis, type of treatment (chemotherapy, +/− surgery; radiotherapy, +/− surgery; both chemo- and radiotherapy, +/− surgery; and surgery only), age group at treatment, and calendar period at treatment. In addition, the prevalence of fertility impairment according to each of the different criteria will be calculated along with that of fertility impairment based on the criteria that evaluate ovarian function (criteria 1 to 6) and possible difficulties getting pregnant (criteria 7 and 8).
Multivariable logistic regression analysis will be used to investigate which diagnostic- or treatment-related risk factors influence the probability of being fertility impaired. All analyses will be adjusted for possible confounders, such as age at the time of study assessment, time since diagnosis, smoking status, BMI, and use of hormonal contraception. Furthermore, to detect possible selection bias, descriptive statistics will be used to describe any differences in age at time of study assessment, age at diagnosis, cancer diagnosis, time since diagnosis, and type of treatment between participants, nonparticipants, and excluded women, as seen in
The case-control study is nested within the cohort study, meaning that both cases and controls are selected from participants of the cohort study. However, only participants from institutions that are able to provide detailed treatment data are potential inclusions for the case-control study. This is the case for participants from 11 out of the 16 cohorts in the cohort study (
The aims of the nested case-control study are to identify specific treatment-related factors associated with an increased risk of fertility impairment among CAYA cancer survivors and investigate possible dose-response relationships between cumulative dose of radiation from radiotherapy, cumulative dose of specific anticancer drugs, and the risk of fertility impairment.
The minimal sample size to be included in the nested case-control study population is calculated
Cases are defined as women who are fertility impaired, as assessed by the 8 criteria described in
Prior to identifying the cases it is estimated that using these 8 criteria, substantially more than the 402 required cases will be identified. Therefore, to include the 402 cases that are most likely to actually be fertility impaired, the decision was made to hierarchically structure these 8 criteria. Moreover, in making this hierarchy, we also considered the certainty by which each criterion can establish whether the remainder of the participants (ie, the
Additional data collected for all selected cases and controls include type, number of cycles, and cumulative doses of each chemotherapeutic agent. For radiotherapy data on site, fractionation schedules and cumulative doses are collected.
Multivariable regression models will be used to investigate which risk factors are most strongly associated with an increased risk of fertility impairment. For this purpose, the associations with individual chemotherapeutic agents and radiotherapy body sites and the risk of fertility impairment will be investigated along with the association with cumulative doses of these chemo- and radiotherapy body sites.
The total base cohort consists of 14,379 female 5-year CAYA cancer survivors, 10,964 of whom are either invited for one of the local fertility studies in the past (n=8500) or for the PanCareLIFE female fertility study (n=2464) (
Number of participants in the cohort study who could potentially meet the criteria of fertility impairment by participating cohort.
Name of study cohort | Criterion 1 (n=1455) | Criterion 2 (n=1566) | Criterion 3 (n=1207) | Criterion 4 (n=3133) | Criterion 5 (n=5861) | Criterion 6 (n=1640) | Criterion 7 (n=2759) | Criterion 8 (n=5050) | |||||||||
DCOG LATER cohort | 615 | 615 | 614 | 1109 | 1109 | 619 | 1109 | 0 | |||||||||
Hodgkin Lymphoma cohort | 0 | 0 | 0 | 203 | 203 | 0 | 0 | 0 | |||||||||
VIVE cohort | 0 | 0 | 0 | 0 | 2482 | 0 | 0 | 2482 | |||||||||
Ewing 2008 Clinical Trials cohort | 22 | 22 | 2 | 46 | 46 | 24 | 46 | 46 | |||||||||
Berlin Hormone Analyses cohort | 69 | 69 | 69 | 83 | 83 | 69 | 0 | 0 | |||||||||
Cohort female 5-y cancer survivors Brno | 180 | 180 | 85 | 182 | 182 | 180 | 182 | 182 | |||||||||
Cohort female 5-y cancer survivors Motole | 236 | 236 | 198 | 574 | 574 | 301 | 574 | 574 | |||||||||
Swiss Childhood Cancer Registry cohort 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 685 | |||||||||
Swiss Childhood Cancer Registry cohort 2 | 0 | 0 | 0 | 0 | 113 | 0 | 0 | 113 | |||||||||
Lymphoma survivor cohort | 0 | 46 | 36 | 0 | 51 | 46 | 51 | 51 | |||||||||
Acute lymphoblastic leukemia survivor cohort | 0 | 65 | 10 | 0 | 82 | 65 | 82 | 82 | |||||||||
Rhone Alpe cohort 1 | 35 | 35 | 9 | 120 | 120 | 35 | 0 | 120 | |||||||||
Rhone Alpe cohort 2 | 62 | 62 | 0 | 101 | 101 | 62 | 0 | 0 | |||||||||
Gaslini female survivors cohort | 122 | 122 | 109 | 563 | 563 | 122 | 563 | 563 | |||||||||
Hematopoietic stem cell transplantation cohort | 42 | 42 | 40 | 50 | 50 | 44 | 50 | 50 | |||||||||
The Edmond and Lily Safra Children’s Hospital Late Effects cohort | 72 | 72 | 35 | 102 | 102 | 73 | 102 | 102 |
Number of cases and controls identified within study cohorts included in the nested case-control study.
Institute | Study cohort |
Cases identified (n=450) | Number of controls matched | |
Controls identified within same cohort (n=801) | Controls identified within DCOG LATER cohort (n=81) | |||
DCOG LATER | DCOG LATER cohort | 120 | 238 | N/Aa |
Westfaelische Wilhelms-Universitaet Muenster | Ewing 2008 Clinical Trials cohort | 8 | 15 | 0 |
Fakultni Nemocinice Brno | Cohort malignant cancer survivors Brno | 17 | 30 | 3 |
Fakultni Nemocnice v Motol | Cohort malignant cancer survivors Motol | 128 | 232 | 19 |
Istituto Giannina Gaslini | Gasline female survivors cohort | 91 | 179 | 2 |
Great Ormond Street Children’s Hospital and University College London Hospital | Hematopoietic stem cell transplantation cohort | 28 | 6 | 43 |
Oslo University Hospital | Lymphoma survivor cohort and Acute lymphoblastic leukemia survivor cohort | 18 | 24 | 12 |
University hospital Saint-Étienne | Rhone Alpe cohort 1 and Rhone Alpe cohort 2 | 28 | 56 | 0 |
Edmond and Lily Safra Children’s Hospital, Sheba Medical Center | The Edmond and Lily Safra Children’s Hospital Late Effects cohort | 12 | 21 | 2 |
aN/A: Not applicable.
Results show that within the total group of 6619 participants, criterion 1 could be evaluated among 21.98% (1455/6619) of the participants, criterion 2 among 23.66% (1566/6619), criterion 3 among 18.24% (1207/6619), criterion 4 among 47.33% (3133/6619), criterion 5 among 88.55% (5861/6619), criterion 6 among 24.78% (1640/6619), criterion 7 among 41.68% (2759/ 6619), and criterion 8 among 76.30% (5050/6619) of the participants. However, data providers who collect their data during the course of PanCareLIFE collect data for all 8 criteria. This results in a total group of 464 participants for whom all 8 criteria can successfully be evaluated.
All data are collected and entered into local electronic databases by data providers and sent to the coordinating data center in Mainz (WP1). These data are subsequently checked, merged, and cleaned by investigators from WP1 after which a final, aggregated dataset is sent to the investigators of WP3.
The selection of cases and controls has been successfully performed using the hierarchically-ordered criteria of fertility impairment. However, ultimately, it appears that this hierarchy can be discarded since, after the application of the 8th criterion, a total of 504 cases have been identified from the total eligible cohort. Of these, 13 cases are excluded, because no treatment data are available, and 41 because no appropriate matching controls can be found. Therefore, ultimately, 450 cases are included in the case-control study. If the cases identified by the last criterion (criterion 8) are not included in the nested case-cohort study, this will lead to fewer than the required 402 cases.
The 450 selected cases are matched to 882 controls. Some cohort cases cannot be matched to 2 controls owing to an insufficient number of controls in that cohort. However, because the Dutch Childhood Oncology Group - Long term Effects after Childhood Cancer cohort (see
Data analysis of both the PanCareLIFE cohort study and the case-control study is currently under way and the first results are expected to be submitted for publication in 2019.
This paper describes the design and methods of 2 studies on female fertility within the PanCareLIFE project. Due to the large number of institutions collaborating within this project, these studies will encompass the largest group of CAYA cancer survivors among whom female fertility is investigated using both self-reported and hormonal data. Results will provide detailed insight into the prevalence of fertility impairment following CAYA cancer and the diagnostic- or treatment-related factors associated with an increased risk of fertility impairment. This will help clinicians to adequately counsel both girls or young women who are about to start anticancer treatments as well as adult female CAYA cancer survivors about issues concerning their remaining reproductive life span and the possible need for fertility preservation interventions. Moreover, knowledge gained from the 2 studies can be incorporated into existing evidence-based clinical guidelines on female fertility for CAYA cancer patients and survivors [
The 2 fertility studies conducted within PanCareLIFE have several strengths. First, the international collaboration, as achieved in PanCareLIFE, has resulted in an unprecedented number of female CAYA cancer survivors for whom data on fertility impairment are available. Large study populations are essential to achieve statistically and clinically meaningful results. Moreover, the large sample size in the PanCareLIFE fertility studies will allow many subgroup analyses. For these analyses, survivors whose former treatment is presumed not to negatively affect fertility (as indicated by the literature available at time of data analyses) can serve as the reference group when calculating effect measures, such as relative risks or odds ratios. Second, within both PanCareLIFE fertility studies, a broad definition of fertility impairment has been employed using several criteria that have frequently been used in previous studies assessing fertility in female CAYA cancer survivors [
For the cohort study, survivors are considered
The fertility studies within PanCareLIFE have some limitations. First, due to missing information, some of the data on fertility impairment collected in previous local studies cannot be successfully recoded to make them compatible with the data that are collected with the PanCareLIFE questionnaire. As a consequence, data from some cohorts cannot be considered when calculating the overall prevalence of fertility impairment. Second, our studies may be subject to selection bias because from about 60% of the total invited group of subjects’ outcome data from are available for the cohort study and even less for the nested case-control study. This could impact the generalizability of our study results. To estimate the risk of selection bias, participants will be compared with nonparticipants relative to age at time of study assessment and disease-related characteristics. Third, no information is available on the fertility outcomes of women treated for CAYA cancer who died before the study (after having survived for at least 5 years). Because many of these women might have been treated with relatively high (gonado)toxic treatment regimens, they would most probably have met at least one of the 8 criteria of fertility impairment, were they still living. As a consequence, the risk of fertility impairment calculated based on this study results might be an underestimation of the “true” risk. Furthermore, for some (sub)cohorts, not all self-reported or hormonal data needed to evaluate each of the 8 criteria are available, because these data were not collected during the local fertility study in the past. As a result, survivors within certain cohorts can be evaluated by one or 2 criteria only. Hypothetically, these women could also have met one of the other criteria. However, because data for these other criteria are lacking, this group of women might be misclassified (ie, categorized as being
In summary, the 2 fertility studies conducted within PanCareLIFE will generate evidence-based knowledge concerning risk factors for impaired fertility among female CAYA cancer survivors as well as valuable information regarding differences in the prevalence of fertility impairment using different criteria to define this impairment. These results will enhance clinical practice because they will help health care practitioners provide adequate counseling concerning future parenthood to CAYA cancer survivors as well as new patients and refer these individuals to a reproductive specialist for fertility preservation in a timely manner. The ultimate objective is to empower patients and survivors and improve their quality of life.
Expanded version of
Flow of data collected for the two fertility studies within PanCareLIFE project.
anti-Müllerian hormone
Amsterdam UMC, Vrije Universiteit
childhood, adolescent, and young adult
follicle stimulating hormone
work package
We gratefully thank all the patients and survivors who provided their data for research and for PanCareLIFE. This project received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement number 602030.
PanCareLIFE (Grant Agreement no. 602030) is a collaborative project in the 7th Framework Programme of the European Union. Project partners are: Universitätsmedizin der Johannes Gutenberg-Universität Mainz, Germany (PD Dr P Kaatsch, Dr D Grabow), Boyne Research Institute, Drogheda, Ireland (Dr J Byrne, Ms H Campbell), Pintail Ltd, Dublin, Ireland (Mr C Clissmann, Dr K O’Brien), Academisch Medisch Centrum bij de Universiteitvan Amsterdam, Netherlands (Dr LCM Kremer), Universität zu Lübeck, Germany (Professor T Langer), Stichting VU-VUMC, Amsterdam, Netherlands (Dr E van Dulmen-den Broeder, Dr MH van den Berg), Erasmus Universitair Medisch Centrum Rotterdam, Netherlands (Dr MM van den Heuvel-Eibrink), Charité–Universitätsmedizin Berlin, Germany (PD Dr A Borgmann-Staudt), Westfälische Wilhelms-Universität Münster, Germany (Professor A am Zehnhoff-Dinnesen), Universität Bern, Switzerland (Professor CE Kuehni), Istituto Giannina Gaslini, Genoa, Italy (Dr R Haupt, Dr Monica Muraca), Fakultni nemocnice Brno, Czech Republic (Dr T Kepak), International Clinical Research Center (FNUSA-ICRC) (Dr T Kepak), Centre Hospitalier Universitaire Saint Etienne-CHU, Saint Etienne, France (Dr C Berger), Kraeftens Bekaempelse, Copenhagen, Denmark (Dr JF Winther), Fakultni nemocnice v Motol, Prague, Czech Republic (Dr J Kruseova) and Universitaetsklinikum Bonn, Bonn, Germany (Dr G Calaminus, Dr K Baust). Data are provided by: Academisch Medisch Centrum bij de Universiteit van Amsterdam, on behalf of the DCOG LATER Study centres, Netherlands (Dr LCM Kremer), Stichting VU-VUMC, Amsterdam, Netherlands (Dr E van Dulmen-den Broeder, Dr MH van den Berg), Erasmus Universitair Medisch Centrum Rotterdam, Netherlands (Dr MM van den Heuvel-Eibrink), Prinses Maxima Centrum (Dr MM van den Heuvel-Eibrink), Netheralnds Netherlands Cancer Institute (Professor F van Leeuwen), Charité-Universitätsmedizin Berlin, Germany (PD Dr. A Borgmann-Staudt, Dr G Strauß), Westfälische Wilhelms-Universität Münster, Germany (Professor A am Zehnhoff-Dinnesen, Professor U Dirksen), Universität Bern, Switzerland (Professor CE Kuehni), Istituto Giannina Gaslini, Genoa, Italy (Dr R Haupt, Dr Monica Muraca, Dr M-L Garré), Fakultni nemocnice Brno, Czech Republic (Dr T Kepak), International Clinical Research Center (FNUSA-ICRC) (Dr T Kepak), Centre Hospitalier Universitaire Saint Etienne, France (Dr C Berger), Kraeftens Bekaempelse, Copenhagen, Denmark (Dr JF Winther), Fakultni nemocnice v Motol, Prague, Czech Republic (Dr J Kruseova), Universitetet i Oslo, Norway (Professor S Fosså), Great Ormond Street Hospital (Dr A Leiper), Medizinische Universität Graz, Austria (Professor H Lackner), St Anna Kinderspital, Vienna, Austria (Dr L Kager), Uniwersytet Medyczny w Białymstoku, Bialystok, Poland (Dr A Panasiuk, Dr M Krawczuk-Rybak), Heinrich Heine Universität Düsseldorf, Germany (Dr M Kunstreich, Dr A Borkhardt), Universität Ulm, Germany (Dr H Cario, Professor O Zolk), Universität zu Lübeck, Germany (Professor T Langer), Klinikum Stuttgart, Olgahospital, Stuttgart, Germany (Professor S Bielack), Uniwersytet Gdánski, Poland (Professor J Stefanowicz), University College London Hospital, UK (Dr V Grandage), Sheba Medical Center Hospital, Tel Aviv, Israel (Dr D Modan-Moses) and Universitaetsklinikum Bonn, Bonn, Germany (Dr G Calaminus).
None declared.