OBJECTIVES AND DESIGN: A novel risk stratification algorithm estimating risk of death in patients with relapsed multiple myeloma starting second-line treatment was recently developed using multivariable Cox regression of data from a Czech registry. It uses 16 parameters routinely collected in medical practice to stratify patients into four distinct risk groups in terms of survival expectation. To provide insight into generalisability of the risk stratification algorithm, the study aimed to validate the risk stratification algorithm using real-world data from specifically designed retrospective chart audits from three European countries. PARTICIPANTS AND SETTING: Physicians collected data from 998 patients (France, 386; Germany, 344; UK, 268) and applied the risk stratification algorithm. METHODS: The performance of the Cox regression model for predicting risk of death was assessed by Nagelkerke's R2, goodness of fit and the C-index. The risk stratification algorithm's ability to discriminate overall survival across four risk groups was evaluated using Kaplan-Meier curves and HRs. RESULTS: Consistent with the Czech registry, the stratification performance of the risk stratification algorithm demonstrated clear differentiation in risk of death between the four groups. As risk groups increased, risk of death doubled. The C-index was 0.715 (95% CI 0.690 to 0.734). CONCLUSIONS: Validation of the novel risk stratification algorithm in an independent 'real-world' dataset demonstrated that it stratifies patients in four subgroups according to survival expectation.
- MeSH
- algoritmy MeSH
- hodnocení rizik MeSH
- lidé MeSH
- mnohočetný myelom * MeSH
- retrospektivní studie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Evropa MeSH
- Francie MeSH
- Německo MeSH
INTRODUCTION: Risk stratification tools provide valuable information to inform treatment decisions. Existing algorithms for patients with multiple myeloma (MM) were based on patients with newly diagnosed disease, and these have not been validated in the relapsed setting or in routine clinical practice. We developed a risk stratification algorithm (RSA) for patients with MM at initiation of second-line (2L) treatment, based on data from the Czech Registry of Monoclonal Gammopathies. METHODS: Predictors of overall survival (OS) at 2L treatment were identified using Cox proportional hazards models and backward selection. Risk scores were obtained by multiplying the hazard ratios for each predictor. The K-adaptive partitioning for survival (KAPS) algorithm defined four groups of stratification based on individual risk scores. RESULTS: Performance of the RSA was assessed using Nagelkerke's R2 test and Harrell's concordance index through Kaplan-Meier analysis of OS data. Prognostic groups were successfully defined based on real-world data. Use of a multiplicative score based on Cox modeling and KAPS to define cut-off values was effective. CONCLUSION: Through innovative methods of risk assessment and collaboration between physicians and statisticians, the RSA was capable of stratifying patients at 2L treatment by survival expectations. This approach can be used to develop clinical decision-making tools in other disease areas to improve patient management. FUNDING: Amgen Europe GmbH.
- Publikační typ
- časopisecké články MeSH
Background. We aimed to develop and validate a conceptual model of multiple myeloma (MM) that characterizes the attributes affecting disease progression and patient outcomes, and the relationships between them. Methods. Systematic and targeted literature reviews identified disease- and patient-specific attributes of MM that affect disease progression and outcomes. These attributes were validated by a Delphi panel of four international MM experts, and a physician-validated model was constructed. Real-world clinical data from the Czech Registry of Monoclonal Gammopathies (RMG) was used to confirm the relationships between attributes using pairwise correlations and multiple Cox regression analysis. Results. The Delphi panel reached consensus that most cytogenetic abnormalities influenced disease activity, which results in symptoms and complications and affects overall survival (OS). Comorbidities and complications also affect OS. The entire panel agreed that quality of life was influenced by comorbidities, age, complications, and symptoms. Consensus was not reached in some cases, in particular, the influence of del(17p) on complications. The relationships between attributes were confirmed using pairwise analysis of real-world data from the Czech RMG; most of the correlations identified were statistically significant and the strength of the correlations changed with successive relapses. Czech RMG data were also used to confirm significant predictors of OS included in the model, such as age, Eastern Cooperative Oncology Group performance status, and extramedullary disease. Conclusions. This validated conceptual model can be used for economic modeling and clinical decision making. It could also inform the development of disease-based models to explore the impact of disease progression and treatment on outcomes in patients with MM.
- Publikační typ
- časopisecké články MeSH
INTRODUCTION: Real-world data on patient outcomes and treatment patterns in multiple myeloma (MM) are limited. MATERIALS AND METHODS: The present noninterventional, observational, retrospective analysis of prospectively collected Czech patient medical record data from the Registry of Monoclonal Gammopathies estimated real-world outcomes in adults with a diagnosis of symptomatic MM made between May 2007 and June 2014. RESULTS: In total, 2446 patients had initiated first-line treatment. The median overall survival since the diagnosis (primary endpoint) was 50.3 months (95% confidence interval, 46.1-54.5 months) and decreased with each successive treatment line. A similar trend was observed for progression-free survival and the depth of response. In line with European guidelines and clinical practice, bortezomib-, thalidomide-, and lenalidomide-based regimens were most commonly used across all treatment lines (42.3%, 28.9%, and 18.4%, respectively). In the first line, bortezomib and thalidomide were used most often, with lenalidomide the most commonly used agent in the relapse setting (second to fourth lines). Exploratory analyses revealed that younger age (≤ 65 years), lower international staging system stage, and previous stem cell transplantation were associated with significant improvements in overall and progression-free survival, especially in the early treatment lines. CONCLUSION: The present study is the first analysis of Czech data from the Registry of Monoclonal Gammopathies, and it provides important insights into the real-world management of MM for physicians and healthcare providers.
- MeSH
- analýza přežití MeSH
- bortezomib terapeutické užití MeSH
- doba přežití bez progrese choroby MeSH
- lenalidomid terapeutické užití MeSH
- lidé středního věku MeSH
- lidé MeSH
- mnohočetný myelom mortalita patologie terapie MeSH
- následné studie MeSH
- prospektivní studie MeSH
- protokoly antitumorózní kombinované chemoterapie terapeutické užití MeSH
- registrace statistika a číselné údaje MeSH
- retrospektivní studie MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- staging nádorů MeSH
- thalidomid terapeutické užití MeSH
- transplantace kmenových buněk * MeSH
- věkové faktory MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- pozorovací studie MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Česká republika MeSH
