Post on 27-May-2020
Determinants of survival in children with cancer in
Johannesburg
Nadia Beringer1,3
Kate Gwynneth Bennett1,2,3
Janet Elizabeth Poole1,2,3
Jennifer Ann Geel1,2,3
1Division of Paediatric Haematology and Oncology, Charlotte Maxeke Johannesburg Academic Hospital2Division of Paediatric Haematology and Oncology, Wits Donald Gordon Medical Centre
3Department of Paediatric and Child Health, Faculty of Health Sciences, University of the Witwatersrand
Why Paediatrics?
Introduction
• Rare1
• 80% of cases low- and middle income countries (LMIC)2
• High income countries (HIC): Second commonest cause of
childhood mortality3
1. Childhood and Cancer: Children’s Health and Environment. Available at: www. who.int/ceh/capacity/cancer.pdf. Accessed January 25, 2017.
2. Stefan DC. Epidemiology of childhood cancer and the SACCSG tumour registry. CME. 2010 Jul; 28(7):317-319.
3. Kaatsch P. Epidemiology of childhood cancer. Cancer Treat Rev. 2010 Jun;36(4):277-28
Top 5 causes of death in Africa (WHO):3
4. World Health Organization. Global Health Observatory (GHO) data. Causes of child mortality. Available at:
https://www.who.int/gho/child_health/mortality/causes/en/. Accessed November 16, 2018.
Epidemiology
INCIDENCE (0-15 years):
• High-income countries (HIC): +- 140 per million3
• South Africa: 33.4 - 47.2 per million5
Marked discrepancy in reporting6
3. Kaatsch P. Epidemiology of childhood cancer. Cancer Treat Rev. 2010 Jun;36(4):277-285.
5. Stefan DC, Stones, DK. The South African Paediatric Tumour Registry – 25 years of activity. SAMJ. 2012;102(7):605-606. DOI:10.7196/SAMJ.5719
6. Howard SC, Metzger ML, Wilmas JA, Quintana Y, Pui CH, Robison LL, Ribeiro RC. Childhood cancer epidemiology in low-income countries. Cancer. 2008 Feb;
112(3):461-472
7. The Cancer Atlas. Children in low-income countries continue to have worse cancer-related outcomes than those in high-income countries Available at:
http://canceratlas.cancer.org/the-burden/cancer-in-children//. Accessed November 13, 2018
Overall Survival (OS)
• HIC - dramatic increase in OS over
past 40 years3,8
• Earlier detection, procedures,
multimodal treatment and better
supportive care
• Improved disease understanding (eg
minimal residual disease)
• Targeted therapies
• Meticulous OS documentation HIC:
• Monitoring of treatment advances
• Means to gauge improvement
3. Kaatsch P. Epidemiology of childhood cancer. Cancer Treat Rev. 2010 Jun;36(4):277-285.
8. Stefan DC, Kruger M, Poole J, Steliarova-Foucher E. Childhood cancer incidence in South Africa, 1987-2007. SAMJ. 2015 Nov;105(11):939-947.
9. Ferman S, de Oliveira Santos M, De Oliveria Ferreira JM, de Souza Reis R, Oliveira JFP, Pombo-de-Oliveira MS, et al. Childhood cancer mortality trends in Brazil,
1979-2008. Clinics 2013;68(2):219-224. DOI:10.6061/clinic/2013(02)OA16
Overall Survival (OS)
10. SlideShare. Late effects of childhood cancer treatment. Kerry Moss, MD Connecticut Children’s Medical Center Alex’s Lemonade Stand Foundation November
16, 2014. https://www.slideshare.net/alexslemonade/late-effects-of-childhood-cancer. Accessed: November 16, 2018.
Overall Survival (OS)
Favourable trends less pronounced in less-developed
regions9
Not routinely calculated in LMIC
• Therefore cannot be used as a monitoring tool3,5
• Under-registration multifactorial6
➢ Inaccurate death certificates
➢ Misdiagnosis
➢ Underreporting9
3. Kaatsch P. Epidemiology of childhood cancer. Cancer Treat Rev. 2010 Jun;36(4):277-285.
4. Stefan DC, Stones, DK. The South African Paediatric Tumour Registry – 25 years of activity. SAMJ. 2012;102(7):605-606. DOI:10.7196/SAMJ.571
6. Howard SC, Metzger ML, Wilmas JA, Quintana Y, Pui CH, Robison LL, Ribeiro RC. Childhood cancer epidemiology in low-income countries. Cancer. 2008
Feb; 112(3):461-472
9. Ferman S, de Oliveira Santos M, De Oliveria Ferreira JM, de Souza Reis R, Oliveira JFP, Pombo-de-Oliveira MS, et al. Childhood cancer mortality trends in Brazil,
1979-2008. Clinics 2013;68(2):219-224. DOI:10.6061/clinic/2013(02)OA16
What is a Kaplan-Meier
curve?
What is a Kaplan-Meier
curve?
• Graphical representation of survival data or time-to-event
analysis
• Proportion of patients surviving against time
• Usually drawn in a step function
11. O’Leary Maura, Krailo M, Anderson JR, Reaman GH. Progress in Childhood Cancer: 50 years of research collaboration, a report from the Children’s Oncology
Group. Semin Oncol. 2008 Oct;35(5):484-493.
Acute Lymphoblastic Leukaemia: Children’s Oncology Group (COG)
SEER DATASurveillance, Epidemiology, and End Results (SEER)
• Started in 1973
• Program of the National Cancer Institute (NCI)
• Source of information on the incidence and survival
rates of cancer in the United States
• Document trends, outcomes and improvements12
12. Duggan MA, Anderson WF, Altekruse S, Penberthy L Sherman E. The Surveillance, Epidemiology and End Results (SEER) Program and Pathology:
Towards Strengthening the Critical Relationship. Am J Surg Pathol. 2016 Dec; 40912):e94-e102. doi:10.1097/PAS.0000000000000749.
13. National cancer institute. Annual Report to the Nation 2017: Special section: Survival. Available at https://seer.cancer.gov/report_to_nation/survival.html. Accessed
November 14, 2018
The setting
South Africa
• UMIC5,9
• Childhood cancer mortality unknown8,14
• Fragmented two-tiered health care system
• Inconsistent access to specialised medical services (state
vs. private)
• Possible discrepancies
8. Stefan DC, Kruger M, Poole J, Steliarova-Foucher E. Childhood cancer incidence in South Africa, 1987-2007. SAMJ. 2015 Nov;105(11):939-947.
14. Statistics South Africa. 2015. Midyear estimates - 2015. Statistical release P0302. [Online] Available at:
http://www.statssa.gov.za/publications/P0302/P03022015.pdf. Accessed July15, 2017.
Wits Donald Gordon Medical Centre
(WDGMC)
Charlotte Maxeke Johannesburg
Academic Hospital (CMJAH)
Proximity
WDGMCRest of Africa
CMJAH
WDGMC vs. CMJAH
Isolation
Better equipment
Access to more supportive care
Occasional experimental
agents
Registrars always available
Casualty
MDT
Same
doctors
Same
treatment
protocols
Objectives
• Describe and compare patient populations at a state vs.
private hospital
• Analyse survival rates
• Determine prognostic factors
• Compare statistics with other countries (UIC)
Methods• Retrospective review
• Patient files retrieved (filing cabinets/archives)
• Patients 0-15 years diagnosed with a malignancy at CMJAH
and WDGMC
• 1 January 2012 - 31 December 2016
• Parameters: demographics, ethnicity and race, hospital at
presentation, diagnosis, stage at presentation, nutrition, HIV status,
patient outcome, follow-up time
Data Analysis• De-identified
• Descriptive analysis
• Mann Whitney U test
• Kaplan-Meier OS curves
• Cox regression
• Univariate and Multivariate analysis
• OS: 1,2 & 5 year OS probability
• Significance level: p < 0.05
Results
Study Patients
270
416
WDGMC CMJAH
Total number = 686
Study Patients
413
268
WDGMC CMJAH
Total number = 681
Ethnicity
0
125
250
375
500
Black White Indian Coloured
3838
119
486
Ethnicity
0
0,2
0,4
0,6
0,8
Black White Indian Coloured
6%6%
17%
71%
Demographics
54%46%
Sex
Male Female
626
4218
0
175
350
525
700
Negative Positive Unknown
HIV Status
SA HIV prevalence
15. South African National HIV prevalance, Incidence and Behaviour Survey, 2012. [Online] Available at:
www.hsrc.ac.za/uploads/pageContent/4565/SABSSM%20IV%20LEO%20final.pdf Accessed June15, 2018.
SA HIV incidence
15. South African National HIV prevalance, Incidence and Behaviour Survey, 2012. [Online] Available at:
www.hsrc.ac.za/uploads/pageContent/4565/SABSSM%20IV%20LEO%20final.pdf Accessed June15, 2018.
Nutrition
CMJAH
15%3%
7%
22%
54%
Normal Weight Underweight
Overweight Obese
Unknown
WDGMC
6%8%
12%
15%
59%
Normal Weight Underweight
Overweight Obese
Unknown
Classification of malignancies
• Classification based on morphology rather than site of
origin (adults)
• INTERNATIONAL CLASSIFICATION OF
CHILDHOOD CANCER, THIRD EDITION
• Standardize international, epidemiological studies and
cancer registries
16. Steliarova-Foucher E, Stiller C, Lacour B. Kaatsch P. 2005. International Classification of Childhood Cancer, Third Edition. American
Cancer Society 103(7):1457-1466 DOI:10.1002/cncr.20910
ICCC-3rd EditionDIAGNOSTIC GROUP NUMBERS
I Leukemias, myeloproliferative disease and myelodysplastic diseases 168
II Lymphomas and reticuloendothelial neoplasm 92
III CNS and miscellaneous intracranial and intraspinal neoplasm 130
IV Neuroblastoma and other peripheral nervous cell tumours 35
V Retinoblastoma 35
VI Renal tumors 66
VII Hepatic tumors 9
VIII Malignant bone tumors 29
IX Soft tissue and other extraosseous sarcoma 68
X Germ cell tumors, trophoblastic tumors, and neoplasms of gonads 30
XI Other malignant epithelial neoplasms and malignant melanomas 15
XII Other and unspecified malignant neoplasms 4
TOTAL 681
Stage at presentation
Neuroblastoma
I
II
III
IV
0 4 7 11 14
CMJAH WDGMC
Renal tumours
I
II
III
IV
V
0 5 9 14 18
CMJAH WDGMC
Stage at presentationSoft tissue and other extraosseous
sarcoma
I
II
III
IV
0 4 7 11 14
CMJAH WDGMC
Early stage: Stage I and II
WDGMC: 41% Early stage
CMJAH: 48% Early stage
DEATHS (early stage):
CMJAH: 10%
WDGMC: 0%
14.5% overall
Renal Tumours
0
10
20
30
40
50
60
70
80
90
100
OS - Renal tumours
0 1 2 3 4 5
Time (years)
Surv
ival pro
babili
ty (
%)
Stage
1
2
3
4
5
Neuroblastoma
0
10
20
30
40
50
60
70
80
90
100
OS - Neuroblastoma
0 1 2 3 4 5
Time (years)
Surv
ival pro
babili
ty (
%)
Stage
1
2
3
4
Overall Survival - Stage
0
10
20
30
40
50
60
70
80
90
100
Overall Survival - Stage
0 1 2 3 4 5
Time (years)
Su
rviv
al p
rob
ab
ility
(%
)
Stage
1
2
3
4
5
p < 0.0001
Late tumour stage at
presentation
???• Difficult to assess retrospectively
• MOSTLY delayed referrals
• Often late medical referrals (peripheral hospitals,
general practioners etc.)
• NOT commonly parents/caregivers
Overall Survival
Median patient follow-up: 2.1 years (IQR 0.7 to 4.55 years)
1 year OS
= 70%5 year OS
= 55%
2 year OS
= 62%
0
10
20
30
40
50
60
70
80
90
100Overall Survival - Hospital
0 1 2 3 4 5
Time (years)
Su
rviv
al p
rob
ab
ility
(%
)
CMJAH
WDGMC
CMJAH
5 year OS = 49%
WDGMC
5 year OS = 62%
p = 0.002
Comparing OS…
1 year OS
= 70%
5 year OS
= 55%
2 year OS
= 62%
Our study: SA Japan: UIC
15. Sugiyama H, Nishi N, Kuwabara M, Ninomiya M, Arita K, Yasui W, et al. Incidence and survival of childhood cancer cases diagnosed between 1998 and
2000 in Hiroshima City, Japan. APJCP, 2009 Oct; 10(4):675-680.
United Kingdom Statistics
17. Cancer Research UK. Children’s cancers survival statistics. Available at: https://www.cancerresearchuk.org/. Accessed November 10, 2018.
Why is our OS not higher?
• Is it demographics,
ethnicity, nationality, HIV
status, sex, nutrition,
hospital stage?????
Some possible factors…
0
10
20
30
40
50
60
70
80
90
100
Overall Survival - Nationality
0 1 2 3 4 5
Time (years)
Surv
ival pro
babili
ty (
%)
South African
Foreign
0
10
20
30
40
50
60
70
80
90
100Overall Survival - Ethnicity
0 1 2 3 4 5
Time (years)
Su
rviv
al p
rob
ab
ility
(%
)
Black
Coloured
White
Indian
0
10
20
30
40
50
60
70
80
90
100Overall Survival - HIV status
0 1 2 3 4 5
Time (years)
Su
rviv
al p
rob
ab
ility
(%
)
HIV negative
HIV positive
Unknown
Possible factors cont…
0
10
20
30
40
50
60
70
80
90
100Overall Survival - Nutrition
0 1 2 3 4 5
Time (years)
Su
rviv
al p
rob
ab
ility
(%
)
Healthy weight
Unhealthy weight
Unknown
0
10
20
30
40
50
60
70
80
90
100Overall Survival - Hospital
0 1 2 3 4 5
Time (years)
Su
rviv
al p
rob
ab
ility
(%
)
CMJAH
WDGMC
Cox Regression AnalysisPotential prognostic factor Univariate analysis
Ethnicity < 0.0001
Nationality 0.037
HIV status 0.32
Nutritional status < 0.0001
Stage at presentation < 0.0001
Hospital 0.002
Cox Regression AnalysisPotential prognostic factors Univariate analysis Multivariate analysis
Ethnicity < 0.0001 0.043
Nationality 0.037 0.130
HIV status 0.32 0.325
Nutritional status < 0.0001 0.009
Stage at presentation < 0.0001 <0.0001
Hospital 0.002 0.441
OS: Nutrition per hospital
0
10
20
30
40
50
60
70
80
90
100Overall Survival (CMJAH) - Nutrition
0 1 2 3 4 5
Time (years)
Su
rviv
al p
rob
ab
ility
(%
)
Normal weight
Underweight
Overweight
Obese
Unknown
P < 0.0001
0
10
20
30
40
50
60
70
80
90
100Overall Survival (WDGMC) - Nutrition
0 1 2 3 4 5
Time (years)
Su
rviv
al p
rob
ab
ility
(%
)
Normal weight
Underweight
Overweight
Obese
Unknown
P < 0.0001
Overall Survival: Tumour type
HL-Hodgkin Lymphoma, NHL-Non-Hodgkin Lymphoma, ALL-Acute Lymphoblastic Leukaemia, AML-Acute Myeloblastic Leukaemia
p = 0.0005
Acute Lymphoblastic
Leukaemia – COG (USA)
0
10
20
30
40
50
60
70
80
90
100
Overall Survival - ALL
0 1 2 3 4 5
Time (years)
Surv
ival pro
babili
ty (
%)
Overall Survival: Tumour type
p < 0.0001
Retinoblastoma – OS
(South Africa)
16. Kruger M, Reynders D, Omar F, Schoeman J, Wedi O, Harvey J. Retinoblastoma outcome at a single institution in South Africa. SAMJ. 2014 Dec;
104(12):859-863
0
10
20
30
40
50
60
70
80
90
100
Overall Survival - Retinoblastoma
0 1 2 3 4 5
Time (years)
Surv
ival pro
bability (
%)
Causes of Death
20%
51%
23%
3% 2% Treatment Related
Mortality
Disease Progression
Relapse
Other Unknown
Causes of Death
1%
3%
24%
52%
20%
Treatment
Related Mortality
Disease Progression
Relapse
Other Unknown
Causes of Death
1%
3%
24%
52%
20%
Treatment
Related Mortality
Disease Progression
Relapse
OtherUnknown
Treatment Related Mortality
• 20% of deaths
• Definition limitations and principal investigator bias
• Chemotherapy toxicities
• Neutropaenic sepsis
ONCOLOGICAL EMERGENCY
• Supportive care necessary: ICU, High care, Isolation
Disease progression
• 52% of deaths
• Late presentation, Late stage
• AREA to be targeted… improve overall survival
• Awareness programs
Limitations• Retrospective audit problems:
• Nutritional data incomplete – definitions were applied
retrospectively
• Tumour staging – some done retrospectively
• Causes of death – TRM definition?
• Race issue – how is it classified?
• Median follow-up time was short - need time for data to
mature
• Only two centres
Recommendations• National study
• Analyse nutrition more closely
• Anabolic vs. Catabolic state
• Evaluate causes of death more closely
• Tease out TRM
• Improve access to supportive care
• Ongoing awareness programmes to increase earlier
detection
Special Thanks
Susan Kriel
Patricia Gomomo
Portia Luaba
Kate Bennett
Jennifer Geel
All medical and nursing colleagues at the two hospitals
Thank you