Long-term survival after childhood acute lymphoblastic leukaemia: population-based trends in cure and relapse by clinical characteristics
Corresponding Author
Lesley Smith
Clinical and Population Sciences Department, School of Medicine, University of Leeds, Leeds, UK
Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
Correspondence: Lesley Smith, Clinical and Population Sciences Department School of Medicine, Room 8.49 Worsley Building, Clarendon Way, University of Leeds, Leeds LS2 9JT, UK.
E-mail: [email protected]
Search for more papers by this authorAdam W. Glaser
Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
Leeds Institute of Cancer and Pathology, School of Medicine, University of Leeds, Leeds, UK
Leeds General Infirmary, Leeds Teaching Hospitals NHS Trust, Leeds, UK
Search for more papers by this authorSally E. Kinsey
Leeds Institute of Cancer and Pathology, School of Medicine, University of Leeds, Leeds, UK
Leeds General Infirmary, Leeds Teaching Hospitals NHS Trust, Leeds, UK
Search for more papers by this authorDarren C. Greenwood
Clinical and Population Sciences Department, School of Medicine, University of Leeds, Leeds, UK
Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
Search for more papers by this authorLucy Chilton
Wolfson Childhood Cancer Research Centre, Northern Institute for Cancer Research, Newcastle University, Newcastle, UK
Search for more papers by this authorAnthony V. Moorman
Wolfson Childhood Cancer Research Centre, Northern Institute for Cancer Research, Newcastle University, Newcastle, UK
Search for more papers by this authorRichard G. Feltbower
Clinical and Population Sciences Department, School of Medicine, University of Leeds, Leeds, UK
Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
Search for more papers by this authorCorresponding Author
Lesley Smith
Clinical and Population Sciences Department, School of Medicine, University of Leeds, Leeds, UK
Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
Correspondence: Lesley Smith, Clinical and Population Sciences Department School of Medicine, Room 8.49 Worsley Building, Clarendon Way, University of Leeds, Leeds LS2 9JT, UK.
E-mail: [email protected]
Search for more papers by this authorAdam W. Glaser
Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
Leeds Institute of Cancer and Pathology, School of Medicine, University of Leeds, Leeds, UK
Leeds General Infirmary, Leeds Teaching Hospitals NHS Trust, Leeds, UK
Search for more papers by this authorSally E. Kinsey
Leeds Institute of Cancer and Pathology, School of Medicine, University of Leeds, Leeds, UK
Leeds General Infirmary, Leeds Teaching Hospitals NHS Trust, Leeds, UK
Search for more papers by this authorDarren C. Greenwood
Clinical and Population Sciences Department, School of Medicine, University of Leeds, Leeds, UK
Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
Search for more papers by this authorLucy Chilton
Wolfson Childhood Cancer Research Centre, Northern Institute for Cancer Research, Newcastle University, Newcastle, UK
Search for more papers by this authorAnthony V. Moorman
Wolfson Childhood Cancer Research Centre, Northern Institute for Cancer Research, Newcastle University, Newcastle, UK
Search for more papers by this authorRichard G. Feltbower
Clinical and Population Sciences Department, School of Medicine, University of Leeds, Leeds, UK
Leeds Institute for Data Analytics, University of Leeds, Leeds, UK
Search for more papers by this authorSummary
‘Cure models’ offer additional information to traditional epidemiological approaches to assess survival for cancer patients by simultaneously estimating the proportion cured and the survival of those ‘uncured’. The proportion cured is a summary of long-term survival while the median survival time of the uncured provides important information on those who are not long-term survivors. Population-based trends in the cure proportion and survival of the uncured for childhood acute lymphoblastic leukaemia (ALL) by clinical prognostic risk factors were estimated using flexible parametric cure models, based on overall survival and event-free survival. Children aged 1–17 years diagnosed between 1990 and 2011 in Yorkshire, UK, were included (n = 492). The percentage cured increased from 77% (95% confidence interval 70–84%) in 1990–1997 to 89% (84–93%) in 2003–2011, while the median survival time of the uncured decreased from 3·2 years (2·2–4·1 years) to 0·7 years (0–1·5 years). Models based on event-free survival showed a similar trend. The 5-year cumulative incidence of relapse substantially decreased from 35% in 1990–97 to 9% in 2003–2011. These results show selective improvement in survival between 1990 and 2011 with a significant reduction in the risk of relapse alongside a reduced absolute duration of survival for those destined to be uncured.
Conflict of Interest
The authors declare no competing interests.
Supporting Information
| Filename | Description |
|---|---|
| bjh15424-sup-0001-Suppinfo.docxWord document, 192.7 KB |
Table SI. Comparison of patient characteristics for those linked and not linked to cytogenetic risk group data, n (%). Table SII. Adjusted differences in the percentage cured and median survival time of uncured [including 95% confidence intervals (CI)] based on overall survival and event free survival for ALL patients. Table SIII. Unadjusted and adjusted survival model results (Excess Mortality Rate Ratio (EMMR), (including 95% confidence intervals (CI))) without cure assumption. Figure S1. Overall survival by cytogenetic risk group, for ALL patients in Yorkshire, 1990–2011, aged 1–17 years. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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