| Título : |
Prognostic value of PET/CT in newly diagnosed multiple myeloma: A Bayesian analysis with missing data imputation |
| Tipo de documento : |
documento electrónico |
| Autores : |
Kenny Mauricio Gálvez Cárdenas, Autor ; González Artunduaga, Eliana Andrea, Autor ; Cruz Gutiérrez, Nelson Alirio, Autor ; Sandoval Álvarez, Simón, Autor |
| Fecha de publicación : |
2025 |
| Títulos uniformes : |
Cancer Research
|
| Idioma : |
Inglés (eng) |
| Resumen : |
Introduction PET/CT assessment in newly diagnosed patients with multiple myeloma is a significant predictor of long-term clinical outcomes. Incorporating this imaging technique into a Bayesian analysis that addresses data gaps allows for more accurate prognostic estimates. This methodology enhances our understanding of the disease and guides informed clinical decisions, ultimately improving patient care. Objective This study aims to evaluate the prognostic value of PET/CT in newly diagnosed patients with multiple myeloma, using Bayesian analysis to manage missing data imputation. We seek to determine how PET/CT findings predict long-term clinical outcomes, thereby enhancing treatment personalization. Hypotheses: A positive PET/CT at diagnosis may correlate with poor prognosis, indicating lower survival rates and worse disease control. A negative PET/CT at diagnosis may be associated with better prognosis, suggesting higher treatment response rates and longer survival. Study Design An analytical study based on clinical and imaging data from PET/CT. Study Population Patients diagnosed with multiple myeloma between 2017 and 2024 at an institution in Medellín, Colombia, approved by the ethics committee of Pablo Tobón Hospital. Variables of Interest: Clinical Variables: Age, sex, type of treatment. PET/CT Variables: Positive (+), negative (-). Other Variables: Cytogenetics, Beta 2 Microglobulin (B2M), Bone Marrow Biopsy, Albumin, Hemoglobin. Outcome Variables: Overall Survival, Progression-Free Survival, Treatment Response. Data Imputation Methodology Using advanced R tools, including: MCMC: For parameter estimation despite incomplete data. SMC: To optimize sequential inferences and improve precision. Statistical Analysis: Kaplan-Meier survival curves for visualizing survival rates. Significance of covariates evaluated through 95% credibility intervals. Results The Bayesian model highlights PET/CT and cytogenetics as key outcome variables. A negative PET/CT correlates with better survival and more accurate treatment response prediction, while a positive PET/CT is linked to higher disease progression rates. Limitations Generalizability may be limited due to single-institution data. Missing data could introduce bias despite imputation methods. Short follow-up may restrict long-term outcome assessment. Variability in imaging protocols may affect result consistency. Conclusions Prognostic Value of PET/CT: The study indicates that PET/CT evaluation is a significant predictor of long-term outcomes in multiple myeloma. A negative PET/CT is linked to better prognosis and treatment response. Clinical Decision Making: Integrating Bayesian analysis and data imputation into PET/CT assessment enhances prognostic accuracy, providing clinicians with valuable insights for personalized treatment and optimized patient care. Citation Format Eliana Andrea González Artunduaga, Nelson Alirio Cruz Gutiérrez, Simón Sandoval Álvarez, Kenny Mauricio Gálvez Cárdenas. Prognostic value of PET/CT in newly diagnosed multiple myeloma: A Bayesian analysis with missing data imputation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4516. |
| Mención de responsabilidad : |
Eliana Andrea González Artunduaga; Nelson Alirio Cruz Gutiérrez; Simón Sandoval Álvarez; Kenny Mauricio Gálvez Cárdenas |
| Referencia : |
Cancer Res (2025) 85 (8_Supplement_1): 4516. |
| DOI (Digital Object Identifier) : |
10.1158/1538-7445.AM2025-4516 |
| Derechos de uso : |
CC BY-NC-ND |
| En línea : |
https://aacrjournals.org/cancerres/article/85/8_Supplement_1/4516/757005 |
| Enlace permanente : |
https://hospitalpablotobon.cloudbiteca.com/pmb/opac_css/index.php?lvl=notice_dis |
Prognostic value of PET/CT in newly diagnosed multiple myeloma: A Bayesian analysis with missing data imputation [documento electrónico] / Kenny Mauricio Gálvez Cárdenas, Autor ; González Artunduaga, Eliana Andrea, Autor ; Cruz Gutiérrez, Nelson Alirio, Autor ; Sandoval Álvarez, Simón, Autor . - 2025. Obra : Cancer ResearchIdioma : Inglés ( eng)
| Resumen : |
Introduction PET/CT assessment in newly diagnosed patients with multiple myeloma is a significant predictor of long-term clinical outcomes. Incorporating this imaging technique into a Bayesian analysis that addresses data gaps allows for more accurate prognostic estimates. This methodology enhances our understanding of the disease and guides informed clinical decisions, ultimately improving patient care. Objective This study aims to evaluate the prognostic value of PET/CT in newly diagnosed patients with multiple myeloma, using Bayesian analysis to manage missing data imputation. We seek to determine how PET/CT findings predict long-term clinical outcomes, thereby enhancing treatment personalization. Hypotheses: A positive PET/CT at diagnosis may correlate with poor prognosis, indicating lower survival rates and worse disease control. A negative PET/CT at diagnosis may be associated with better prognosis, suggesting higher treatment response rates and longer survival. Study Design An analytical study based on clinical and imaging data from PET/CT. Study Population Patients diagnosed with multiple myeloma between 2017 and 2024 at an institution in Medellín, Colombia, approved by the ethics committee of Pablo Tobón Hospital. Variables of Interest: Clinical Variables: Age, sex, type of treatment. PET/CT Variables: Positive (+), negative (-). Other Variables: Cytogenetics, Beta 2 Microglobulin (B2M), Bone Marrow Biopsy, Albumin, Hemoglobin. Outcome Variables: Overall Survival, Progression-Free Survival, Treatment Response. Data Imputation Methodology Using advanced R tools, including: MCMC: For parameter estimation despite incomplete data. SMC: To optimize sequential inferences and improve precision. Statistical Analysis: Kaplan-Meier survival curves for visualizing survival rates. Significance of covariates evaluated through 95% credibility intervals. Results The Bayesian model highlights PET/CT and cytogenetics as key outcome variables. A negative PET/CT correlates with better survival and more accurate treatment response prediction, while a positive PET/CT is linked to higher disease progression rates. Limitations Generalizability may be limited due to single-institution data. Missing data could introduce bias despite imputation methods. Short follow-up may restrict long-term outcome assessment. Variability in imaging protocols may affect result consistency. Conclusions Prognostic Value of PET/CT: The study indicates that PET/CT evaluation is a significant predictor of long-term outcomes in multiple myeloma. A negative PET/CT is linked to better prognosis and treatment response. Clinical Decision Making: Integrating Bayesian analysis and data imputation into PET/CT assessment enhances prognostic accuracy, providing clinicians with valuable insights for personalized treatment and optimized patient care. Citation Format Eliana Andrea González Artunduaga, Nelson Alirio Cruz Gutiérrez, Simón Sandoval Álvarez, Kenny Mauricio Gálvez Cárdenas. Prognostic value of PET/CT in newly diagnosed multiple myeloma: A Bayesian analysis with missing data imputation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4516. |
| Mención de responsabilidad : |
Eliana Andrea González Artunduaga; Nelson Alirio Cruz Gutiérrez; Simón Sandoval Álvarez; Kenny Mauricio Gálvez Cárdenas |
| Referencia : |
Cancer Res (2025) 85 (8_Supplement_1): 4516. |
| DOI (Digital Object Identifier) : |
10.1158/1538-7445.AM2025-4516 |
| Derechos de uso : |
CC BY-NC-ND |
| En línea : |
https://aacrjournals.org/cancerres/article/85/8_Supplement_1/4516/757005 |
| Enlace permanente : |
https://hospitalpablotobon.cloudbiteca.com/pmb/opac_css/index.php?lvl=notice_dis |
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