Current European/US guidelines recommend that molecular testing in advanced non-small cell lung cancer (aNSCLC) be performed using next-generation sequencing (NGS). However, the global uptake of NGS is limited, largely owing to reimbursement constraints. We compared real-world costs of NGS and single-gene testing (SGT) in nonsquamous aNSCLC. This observational study was conducted across 10 pathology centers in 10 different countries worldwide. Biomarker data collected via structured questionnaires (1 January-31 December 2021) were used to feed micro-costing analyses for three scenarios ['Starting Point' (SP; 2021-2022), 'Current Practice' (CP; 2023-2024), and 'Future Horizons' (FH; 2025-2028)] in both a real-world model, comprising all biomarkers tested by each center, and a standardized model, comprising the same sets of biomarkers across centers. Testing costs (including retesting) encompassed personnel costs, consumables, equipment, and overheads. Overall, 4,491 patients with aNSCLC were evaluated. Mean per-patient costs decreased for NGS relative to SGT over time, with real-world model costs 18% lower for NGS than for SGT in the SP scenario, and 26% lower for NGS than for SGT in the CP scenario. Mean per-biomarker costs also decreased over time for NGS relative to SGT. In the standardized model, the tipping point for the minimum number of biomarkers required for NGS to result in cost savings (per patient) was 10 and 12 in the SP and CP scenarios, respectively. Retesting had a negligible impact on cost analyses, and results were robust to variation in cost parameters. This study provides robust real-world global evidence for cost savings with NGS-based panels over SGT to evaluate predictive biomarkers in nonsquamous aNSCLC when the number of biomarkers to be tested exceeds 10. Widespread adoption of NGS may enable more efficient use of limited healthcare resources.

• Klíčová slova
• NSCLC, cost comparison, next‐generation sequencing, precision medicine, predictive biomarker, single‐gene testing,
• MeSH
• analýza nákladů a výnosů MeSH
• genetické testování * ekonomika   metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• nádorové biomarkery * genetika   MeSH
• nádory plic * genetika   ekonomika   diagnóza   patologie   MeSH
• náklady na zdravotní péči * MeSH
• nemalobuněčný karcinom plic * genetika   ekonomika   diagnóza   patologie   MeSH
• senioři MeSH
• vysoce účinné nukleotidové sekvenování * ekonomika   MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• multicentrická studie MeSH
• pozorovací studie MeSH
• srovnávací studie MeSH
• Názvy látek
• nádorové biomarkery * MeSH

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.

• Klíčová slova
• algorithm, relapsed multiple myeloma, risk stratification, survival, validation,
• 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.

• Klíčová slova
• Algorithm, Multiple myeloma, Prognostic model, Risk, Survival,
• Publikační typ
• časopisecké články MeSH

Multiple myeloma (MM) is a malignancy with varying survival outcomes and drivers of disease progression. Existing MM staging tools were developed using data from newly diagnosed patients. As patient characteristics and disease-related factors change between diagnosis and the initiation of second-line (2L) treatment, an unmet need exists for a tool that can evaluate risk of death at first relapse. We have developed a risk stratification algorithm (RSA) using data from patients with MM who were at 2L. Hazard ratios for independent predictors of overall survival (OS) were derived from a Cox models, and individual patient scores were calculated for total risk. K-adaptive partitioning for survival was used to stratify patients into groups based on their scores. Relative risk doubled with ascending risk group; median OSs for patients in group 1 (lowest risk)-4 (highest risk) were 61·6, 29·6, 14·2 and 5·9 months, respectively. Differences in OS between risk groups were significant. Similar stratification was observed when the RSA was applied to an external validation data set. In conclusion, we have developed a validated RSA that can quantify total risk, frailty risk and disease aggressiveness risk, and stratify patients with MM at 2L into groups with profoundly different survival expectations.

• Klíčová slova
• algorithm, multiple myeloma, overall survival, relapsed, risk stratification,
• MeSH
• algoritmy * MeSH
• analýza přežití MeSH
• hodnocení rizik metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• mnohočetný myelom diagnóza   mortalita   patologie   MeSH
• recidiva MeSH
• registrace MeSH
• senioři MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• validační studie 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.

• Klíčová slova
• Delphi panel, conceptual model, economic modeling, multiple myeloma, systematic literature review,
• 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.

• Klíčová slova
• Czech Republic, MM, RMG, Survival, Treatment patterns,
• 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 protinádorové 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 epidemiologie   MeSH
• Názvy látek
• bortezomib MeSH
• lenalidomid MeSH
• thalidomid MeSH

Multiple myeloma (MM) accounts for 10% of hematological cancers. Stem cell transplantation remains the cornerstone of first-line treatment for eligible patients, but historically, pharmaceutical treatment options for MM have been limited. The proteasome was identified as a target for MM therapy in the early 2000s and, in 2004, the boronic acid proteasome inhibitor bortezomib gained European approval. Bortezomib now plays a major role in MM treatment, but the duration of its use can be limited by toxicities such as peripheral neuropathy and the development of resistance. A new generation of proteasome inhibitors has since entered the treatment landscape: carfilzomib, an epoxyketone-based agent with a distinct mode of action, high clinical efficacy, and lower levels of peripheral neuropathy compared with bortezomib, received approval in 2015 for use in patients with relapsed and/or refractory MM (RRMM). Ixazomib, a second-generation, orally administered, boronic acid proteasome inhibitor, has also been approved for use in patients with RRMM. In just over a decade, proteasome inhibitor-based regimens have become an integral component of MM treatment; with more proteasome inhibitors in development, this remains a vibrant research area with potential to improve the lives of patients with MM in the years to come.

• Klíčová slova
• bortezomib, carfilzomib, multiple myeloma, proteasome, proteasome inhibitor,
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH