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Markov model and markers of small cell lung cancer: assessing the influence of reversible serum NSE, CYFRA 21-1 and TPS levels on prognosis

High serum NSE and advanced tumour stage are well-known negative prognostic determinants of small cell lung cancer (SCLC) when observed at presentation. However, such variables are reversible disease indicators as they can change during the course of therapy. The relationship between risk of death a...

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Autores principales: Boher, J-M, Pujol, J-L, Grenier, J, Daurès, J-P
Formato: Texto
Lenguaje:English
Publicado: Nature Publishing Group 1999
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2362697/
https://www.ncbi.nlm.nih.gov/pubmed/10188885
http://dx.doi.org/10.1038/sj.bjc.6690227
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author Boher, J-M
Pujol, J-L
Grenier, J
Daurès, J-P
author_facet Boher, J-M
Pujol, J-L
Grenier, J
Daurès, J-P
author_sort Boher, J-M
collection PubMed
description High serum NSE and advanced tumour stage are well-known negative prognostic determinants of small cell lung cancer (SCLC) when observed at presentation. However, such variables are reversible disease indicators as they can change during the course of therapy. The relationship between risk of death and marker level and disease state during treatment of SCLC chemotherapy is not known. A total of 52 patients with SCLC were followed during cisplatin-based chemotherapy (the median number of tumour status and marker level assessments was 4). The time-homogeneous Markov model was used in order to analyse separately the prognostic significance of change in the state of the serum marker level (NSE, CYFRA 21-1, TPS) or the change in tumour status. In this model, transition rate intensities were analysed according to three different states: alive with low marker level (state 0), alive with high marker level (state 1) and dead (absorbing state). The model analysing NSE levels showed that the mean time to move out of state ‘high marker level’ was short (123 days). There was a 44% probability of the opposite reversible state ‘low marker level’ being reached, which demonstrated the reversible property of the state ‘high marker level’. The relative risk of death from this state ‘high marker level’ was about 2.24 times greater in comparison with that of state 0 ‘low marker level’ (Wald's test; P < 0.01). For patients in state ‘high marker level’ at time of sampling, the probability of death increased dramatically, a transition explaining the rapid decrease in the probability of remaining stationary at this state. However, a non-nil probability to change from state 1 ‘high marker level’ to the opposite transient level, state 0 ‘low marker level’, was observed suggesting that, however infrequently, patients in state 1 ‘high marker level’ might still return to state 0 ‘low marker level’. Almost similar conclusions can be drawn regarding the three-state model constructed using the tumour response status. For the two cytokeratin markers, the Markov model suggests the lack of a true reversible property of these variables as there was only a very weak probability of a patient returning to state ‘low marker level’ once having entered state ‘high marker level’. In conclusion, The Markov model suggests that the observation of an increase in serum NSE level or a lack of response of the disease at any time during follow-up (according to the homogeneous assumption) was strongly associated with a worse prognosis but that the reversion to a low mortality risk state remains possible. © 1999 Cancer Research Campaign
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spelling pubmed-23626972009-09-10 Markov model and markers of small cell lung cancer: assessing the influence of reversible serum NSE, CYFRA 21-1 and TPS levels on prognosis Boher, J-M Pujol, J-L Grenier, J Daurès, J-P Br J Cancer Regular Article High serum NSE and advanced tumour stage are well-known negative prognostic determinants of small cell lung cancer (SCLC) when observed at presentation. However, such variables are reversible disease indicators as they can change during the course of therapy. The relationship between risk of death and marker level and disease state during treatment of SCLC chemotherapy is not known. A total of 52 patients with SCLC were followed during cisplatin-based chemotherapy (the median number of tumour status and marker level assessments was 4). The time-homogeneous Markov model was used in order to analyse separately the prognostic significance of change in the state of the serum marker level (NSE, CYFRA 21-1, TPS) or the change in tumour status. In this model, transition rate intensities were analysed according to three different states: alive with low marker level (state 0), alive with high marker level (state 1) and dead (absorbing state). The model analysing NSE levels showed that the mean time to move out of state ‘high marker level’ was short (123 days). There was a 44% probability of the opposite reversible state ‘low marker level’ being reached, which demonstrated the reversible property of the state ‘high marker level’. The relative risk of death from this state ‘high marker level’ was about 2.24 times greater in comparison with that of state 0 ‘low marker level’ (Wald's test; P < 0.01). For patients in state ‘high marker level’ at time of sampling, the probability of death increased dramatically, a transition explaining the rapid decrease in the probability of remaining stationary at this state. However, a non-nil probability to change from state 1 ‘high marker level’ to the opposite transient level, state 0 ‘low marker level’, was observed suggesting that, however infrequently, patients in state 1 ‘high marker level’ might still return to state 0 ‘low marker level’. Almost similar conclusions can be drawn regarding the three-state model constructed using the tumour response status. For the two cytokeratin markers, the Markov model suggests the lack of a true reversible property of these variables as there was only a very weak probability of a patient returning to state ‘low marker level’ once having entered state ‘high marker level’. In conclusion, The Markov model suggests that the observation of an increase in serum NSE level or a lack of response of the disease at any time during follow-up (according to the homogeneous assumption) was strongly associated with a worse prognosis but that the reversion to a low mortality risk state remains possible. © 1999 Cancer Research Campaign Nature Publishing Group 1999-03 /pmc/articles/PMC2362697/ /pubmed/10188885 http://dx.doi.org/10.1038/sj.bjc.6690227 Text en Copyright © 1999 Cancer Research Campaign https://creativecommons.org/licenses/by/4.0/This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material.If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/.
spellingShingle Regular Article
Boher, J-M
Pujol, J-L
Grenier, J
Daurès, J-P
Markov model and markers of small cell lung cancer: assessing the influence of reversible serum NSE, CYFRA 21-1 and TPS levels on prognosis
title Markov model and markers of small cell lung cancer: assessing the influence of reversible serum NSE, CYFRA 21-1 and TPS levels on prognosis
title_full Markov model and markers of small cell lung cancer: assessing the influence of reversible serum NSE, CYFRA 21-1 and TPS levels on prognosis
title_fullStr Markov model and markers of small cell lung cancer: assessing the influence of reversible serum NSE, CYFRA 21-1 and TPS levels on prognosis
title_full_unstemmed Markov model and markers of small cell lung cancer: assessing the influence of reversible serum NSE, CYFRA 21-1 and TPS levels on prognosis
title_short Markov model and markers of small cell lung cancer: assessing the influence of reversible serum NSE, CYFRA 21-1 and TPS levels on prognosis
title_sort markov model and markers of small cell lung cancer: assessing the influence of reversible serum nse, cyfra 21-1 and tps levels on prognosis
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2362697/
https://www.ncbi.nlm.nih.gov/pubmed/10188885
http://dx.doi.org/10.1038/sj.bjc.6690227
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