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Østergaard A, Fiocco M, de Groot-Kruseman H, Moorman AV, Vora A, Zimmermann M, Schrappe M, Biondi A, Escherich G, Stary J, Imai C, Imamura T, Heyman M, Schmiegelow K, Pieters R. ETV6::RUNX1 Acute Lymphoblastic Leukemia: how much therapy is needed for cure? Leukemia 2024; 38:1477-1487. [PMID: 38844578 PMCID: PMC11216990 DOI: 10.1038/s41375-024-02287-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 05/11/2024] [Accepted: 05/14/2024] [Indexed: 07/03/2024]
Abstract
Recent trials show 5-year survival rates >95% for ETV6::RUNX1 Acute Lymphoblastic Leukemia (ALL). Since treatment has many side effects, an overview of cumulative drug doses and intensities between eight international trials is presented to characterize therapy needed for cure. A meta-analysis was performed as a comprehensive summary of survival outcomes at 5 and 10 years. For drug dose comparison in non-high risk trial arms, risk group distribution was applied to split the trials into two groups: trial group A with ~70% (range: 63.5-75%) of patients in low risk (LR) (CCLSG ALL2004, CoALL 07-03, NOPHO ALL2008, UKALL2003) and trial group B with ~45% (range: 38.7-52.7%) in LR (AIEOP-BFM ALL 2000, ALL-IC BFM ALL 2002, DCOG ALL10, JACLS ALL-02). Meta-analysis did not show evidence of heterogeneity between studies in trial group A LR and medium risk (MR) despite differences in treatment intensity. Statistical heterogeneity was present in trial group B LR and MR. Trials using higher cumulative dose and intensity of asparaginase and pulses of glucocorticoids and vincristine showed better 5-year event-free survival but similar overall survival. Based on similar outcomes between trials despite differences in therapy intensity, future trials should investigate, to what extent de-escalation is feasible for ETV6::RUNX1 ALL.
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Affiliation(s)
- Anna Østergaard
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Marta Fiocco
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
- Mathematical Institute, Leiden University, Leiden, The Netherlands
- Department of Biomedical Science, Section Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Hester de Groot-Kruseman
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
- Dutch Childhood Oncology Group (DCOG), Utrecht, The Netherlands
| | - Anthony V Moorman
- Leukaemia Research Cytogenetics Group, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
- United Kingdom Acute Lymphoblastic Leukaemia (UKALL) study group, Liverpool, UK
| | - Ajay Vora
- United Kingdom Acute Lymphoblastic Leukaemia (UKALL) study group, Liverpool, UK
- Department of Haematology, Great Ormond Street Hospital, London, UK
| | - Martin Zimmermann
- Department of Paediatric Haematology and Oncology, Hannover Medical School, 30625, Hannover, Germany
- Berlin-Frankfurt-Münster Study Group (BFM), Frankfurt, Germany
| | - Martin Schrappe
- Berlin-Frankfurt-Münster Study Group (BFM), Frankfurt, Germany
- Department of Paediatrics, University Medical Centre Schleswig-Holstein, Kiel, Germany
| | - Andrea Biondi
- Department of Pediatrics, University of Milano-Bicocca, Monza, Italy
- Associazione Italiana di Ematologia e Oncologia Pediatrica (AIEOP), Bologna, Italy
| | - Gabriele Escherich
- Department of Pediatric Hematology and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Childhood Acute Lymphoblastic Leukemia study group (CoALL), Hamburg, Germany
| | - Jan Stary
- Department of Pediatric Hematology and Oncology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Chihaya Imai
- Department of Pediatrics, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
- Children's Cancer and Leukemia Study Group (CCLSG), Nagoya, Japan
| | - Toshihiko Imamura
- Department of Pediatrics, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan
- Japan Childhood Leukemia Study Group (JACLS), Nagoya, Japan
| | - Mats Heyman
- Childhood Cancer Research Unit, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
- Department of Paediatric Oncology, Karolinska University Hospital, Stockholm, Sweden
- Nordic Society of Paediatric Haematology and Oncology (NOPHO), Nordic Countries, Uppsala, Sweden
| | - Kjeld Schmiegelow
- Department of Pediatrics and Adolescent Medicine, University Hospital Rigshospitalet, Institute of Clinical Medicine, Faculty of Medicine, University of Copenhagen, Copenhagen, Denmark
- Nordic Society of Paediatric Haematology and Oncology (NOPHO), Nordic and Baltic Countries, Uppsala, Sweden
| | - Rob Pieters
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands.
- Dutch Childhood Oncology Group (DCOG), Utrecht, The Netherlands.
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Modelling time-varying covariates effect on survival via functional data analysis: application to the MRC BO06 trial in osteosarcoma. STAT METHOD APPL-GER 2022. [DOI: 10.1007/s10260-022-00647-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
AbstractTime-varying covariates are of great interest in clinical research since they represent dynamic patterns which reflect disease progression. In cancer studies biomarkers values change as functions of time and chemotherapy treatment is modified by delaying a course or reducing the dose intensity, according to patient’s toxicity levels. In this work, a Functional covariate Cox Model (FunCM) to study the association between time-varying processes and a time-to-event outcome is proposed. FunCM first exploits functional data analysis techniques to represent time-varying processes in terms of functional data. Then, information related to the evolution of the functions over time is incorporated into functional regression models for survival data through functional principal component analysis. FunCM is compared to a standard time-varying covariate Cox model, commonly used despite its limiting assumptions that covariate values are constant in time and measured without errors. Data from MRC BO06/EORTC 80931 randomised controlled trial for treatment of osteosarcoma are analysed. Time-varying covariates related to alkaline phosphatase levels, white blood cell counts and chemotherapy dose during treatment are investigated. The proposed method allows to detect differences between patients with different biomarkers and treatment evolutions, and to include this information in the survival model. These aspects are seldom addressed in the literature and could provide new insights into the clinical research.
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Musta E, van Geloven N, Anninga J, Gelderblom H, Fiocco M. Short-term and long-term prognostic value of histological response and intensified chemotherapy in osteosarcoma: a retrospective reanalysis of the BO06 trial. BMJ Open 2022; 12:e052941. [PMID: 35537786 PMCID: PMC9092180 DOI: 10.1136/bmjopen-2021-052941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
OBJECTIVES Cure rate models accounting for cured and uncured patients, provide additional insights into long and short-term survival. We aim to evaluate the prognostic value of histological response and chemotherapy intensification on the cure fraction and progression-free survival (PFS) for the uncured patients. DESIGN Retrospective analysis of a randomised controlled trial, MRC BO06 (EORTC 80931). SETTING Population-based study but proposed methodology can be applied to other trial designs. PARTICIPANTS A total of 497 patients with resectable highgrade osteosarcoma, of which 118 were excluded because chemotherapy was not started, histological response was not reported, abnormal dose was reported or had disease progression during treatment. INTERVENTIONS Two regimens with the same anticipated cumulative dose (doxorubicin 6×75 mg/m2/week; cisplatin 6×100 mg/m2/week) over different time schedules: every 3 weeks in regimen-C and every 2 weeks in regimen-DI. PRIMARY AND SECONDARY OUTCOME MEASURES The primary outcome is PFS computed from end of treatment because cure, if it occurs, may happen at any time during treatment. A mixture cure model is used to study the effect of histological response and intensified chemotherapy on the cure status and PFS for the uncured patients. RESULTS Histological response is a strong prognostic factor for the cure status (OR 3.00, 95% CI 1.75 to 5.17), but it has no clear effect on PFS for the uncured patients (HR 0.78, -95% CI 0.53 to 1.16). The cure fractions are 55% (46%-63%) and 29% (22%-35%), respectively, among patients with good and poor histological response (GR, PR). The intensified regimen was associated with a higher cure fraction among PR (OR 1.90, 95% CI 0.93 to 3.89), with no evidence of effect for GR (OR 0.78, 95% CI 0.38 to 1.59). CONCLUSIONS Accounting for cured patients is valuable in distinguishing the covariate effects on cure and PFS. Estimating cure chances based on these prognostic factors is relevant for counselling patients and can have an impact on treatment decisions. TRIAL REGISTRATION NUMBER ISRCTN86294690.
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Affiliation(s)
- Eni Musta
- Korteweg-de Vries Institute for Mathematics, University of Amsterdam, Amsterdam, The Netherlands
| | - Nan van Geloven
- Department of Biomedical Data Science, Leiden University Medical Center, Leiden, The Netherlands
| | - Jakob Anninga
- Department of Solid Tumours, Princess Máxima Centre, Utrecht, The Netherlands
| | - Hans Gelderblom
- Department of Medical Oncology, Leiden University Medical Center, Leiden, The Netherlands
| | - Marta Fiocco
- Department of Biomedical Data Science, Leiden University Medical Center, Leiden, The Netherlands
- Department of Solid Tumours, Princess Máxima Centre, Utrecht, The Netherlands
- Mathematical Institute, Leiden University, Leiden, The Netherlands
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Lilienthal I, Herold N. Targeting Molecular Mechanisms Underlying Treatment Efficacy and Resistance in Osteosarcoma: A Review of Current and Future Strategies. Int J Mol Sci 2020; 21:ijms21186885. [PMID: 32961800 PMCID: PMC7555161 DOI: 10.3390/ijms21186885] [Citation(s) in RCA: 157] [Impact Index Per Article: 39.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 09/13/2020] [Accepted: 09/15/2020] [Indexed: 12/12/2022] Open
Abstract
Osteosarcoma is the most common primary malignant bone tumour in children and adolescents. Due to micrometastatic spread, radical surgery alone rarely results in cure. Introduction of combination chemotherapy in the 1970s, however, dramatically increased overall survival rates from 20% to approximately 70%. Unfortunately, large clinical trials aiming to intensify treatment in the past decades have failed to achieve higher cure rates. In this review, we revisit how the heterogenous nature of osteosarcoma as well as acquired and intrinsic resistance to chemotherapy can account for stagnation in therapy improvement. We summarise current osteosarcoma treatment strategies focusing on molecular determinants of treatment susceptibility and resistance. Understanding therapy susceptibility and resistance provides a basis for rational therapy betterment for both identifying patients that might be cured with less toxic interventions and targeting resistance mechanisms to sensitise resistant osteosarcoma to conventional therapies.
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Affiliation(s)
- Ingrid Lilienthal
- Division of Paediatric Oncology, Department of Women’s and Children’s Health, Karolinska Institutet, SE-171 76 Stockholm, Sweden
- Correspondence: (I.L.); (N.H.); Tel.: +46-(0)8-52483204 (I.L. & N.H.)
| | - Nikolas Herold
- Division of Paediatric Oncology, Department of Women’s and Children’s Health, Karolinska Institutet, SE-171 76 Stockholm, Sweden
- Paediatric Oncology, Astrid Lindgren’s Children Hospital, Karolinska University Hospital, SE-171 76 Stockholm, Sweden
- Correspondence: (I.L.); (N.H.); Tel.: +46-(0)8-52483204 (I.L. & N.H.)
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Lancia C, Anninga JK, Sydes MR, Spitoni C, Whelan J, Hogendoorn PCW, Gelderblom H, Fiocco M. A novel method to address the association between received dose intensity and survival outcome: benefits of approaching treatment intensification at a more individualised level in a trial of the European Osteosarcoma Intergroup. Cancer Chemother Pharmacol 2019; 83:951-962. [PMID: 30879111 PMCID: PMC6458990 DOI: 10.1007/s00280-019-03797-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Accepted: 02/08/2019] [Indexed: 01/05/2023]
Abstract
PURPOSE There is lack of consensus on the prognostic value of received high dose intensity in osteosarcoma survivorship. Many studies have not shown a clear survival benefit when dose intensity is increased. The aim of this study is to go beyond chemotherapy intensification by arm-wide escalation of intended dose and/or compression of treatment schedule, while conversely addressing the relationship between treatment intensity and survival at the patient level. The study focusses on the difference in outcome results, based on a novel, progressively more individualised approach to dose intensity. METHODS A retrospective analysis of data from MRC BO06/EORTC 80931 randomised controlled trial for treatment of osteosarcoma was conducted. Three types of post hoc patient groups are formed using the intended regimen: the individually achieved cumulative dose and time on treatment, and the increase of individual cumulative dose over time. Event-free survival is investigated and compared in these three stratifications. RESULTS The strata of intended regimen and achieved treatment yields equivalent results. Received cumulative dose over time produces groups with evident different survivorship characteristics. In particular, it highlights a group of patients with an estimated 3-year event-free survival much larger (more than 10%) than other patient groups. This group mostly contains patients randomised to an intensified regimen. In addition, adverse events reported by that group show the presence of increased preoperative myelotoxicity. CONCLUSIONS The manuscript shows the benefits of analyzing studies by using longitudinal data, e.g. recorded per cycle. This has impact on the drafting of future trials by showing why such a level of detail is needed for both treatment and adverse event data. The novel method proposed, based on cumulative dose received over time, shows that longitudinal treatment data might be used to link survival outcome with drug metabolism. This is particularly valuable when pharmacogenetics data for metabolism of cytotoxic agents are not collected. TRIAL REGISTRATION ISRCTN86294690.
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Affiliation(s)
- Carlo Lancia
- Mathematical Institute Leiden University, Niels Bohrweg 1, 2333 CA Leiden, The Netherlands
| | - Jakob K. Anninga
- Department Paediatric Oncology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Matthew R. Sydes
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, UCL and MRC London Hub for Trials Methodology Research, 90 High Holborn, London, WC1V 6LJ UK
| | - Cristian Spitoni
- Mathematical Institute Utrecht University, Budapestlaan 6, 3584 CD Utrecht, The Netherlands
- Department of Epidemiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Jeremy Whelan
- Department of Oncology, University College London Hospital, 235 Euston Rd, Fitzrovia, London, NW1 2BU UK
| | - Pancras C. W. Hogendoorn
- Department of Pathology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, The Netherlands
| | - Hans Gelderblom
- Department of Medical Oncology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, The Netherlands
| | - Marta Fiocco
- Mathematical Institute Leiden University, Niels Bohrweg 1, 2333 CA Leiden, The Netherlands
- Department of Biomedical Data Science, Section Medical Statistics, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, The Netherlands
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