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A novel method for interpreting survival analysis data: description and test on three major clinical trials on cardiovascular prevention
BACKGROUND: Major results of randomized clinical trials on cardiovascular prevention are currently provided in terms of relative or absolute risk reductions, including also the number needed to treat (NNT), incorrectly implying that a treatment might prevent the occurrence of the outcome/s under inv...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7318394/ https://www.ncbi.nlm.nih.gov/pubmed/32586346 http://dx.doi.org/10.1186/s13063-020-04511-y |
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author | Mengozzi, Alessandro Tricò, Domenico Natali, Andrea |
author_facet | Mengozzi, Alessandro Tricò, Domenico Natali, Andrea |
author_sort | Mengozzi, Alessandro |
collection | PubMed |
description | BACKGROUND: Major results of randomized clinical trials on cardiovascular prevention are currently provided in terms of relative or absolute risk reductions, including also the number needed to treat (NNT), incorrectly implying that a treatment might prevent the occurrence of the outcome/s under investigation. Provided that these results are based on survival analysis, the primary measure of which is time-to-the outcome and not the outcome itself, we sought an alternative method to describe, analyse and interpret clinical trial results consistent with this assumption, so as to better define qualitative and quantitative heterogeneity of various therapeutic strategies in terms of their effects and costs. METHODS: The original Kaplan-Meier graphs of three major positive cardiovascular prevention trials (PROVE-IT, LIFE and HOPE) were captured from the PDF images of the article and then digitalized. We calculated the difference between the placebo and active treatment curves and plotted it as a function of time to describe the event-free time gain (Time-Gain) produced by the active treatment. By calculating the exposure to the active treatment in terms of months (MoT) as a function of time and dividing it for the corresponding time-dependent number of event-free years gained (i.e. months/12), we described the kinetics of the pharmaco-economic index MoT/y(+). The same procedure was repeated replacing MoT with the actual number of patients being treated at each time point as a function of time to obtain the NNT to gain 1 event-free year (NNT/y(+)) curve. RESULTS: The Time-Gain curves depict the kinetics of the treatment-related effect over time and possess the peculiar feature of being smooth and accurately fitted by second-order polynomial functions (a*time(2) + b*time); similarly, also the MoT/y(+) and NNT/y(+) curves can be accurately fitted by power functions (a*time(b)). These curves and indices allow to fully appreciate the quantitative and qualitative heterogeneity, both in terms of effects and costs, of the different therapeutic strategies adopted in the three trials. CONCLUSIONS: With our novel method, by exploiting original Kaplan-Meier curves from three major clinical trials on cardiovascular prevention, we generate new information on the actual consequences of choosing a therapeutic strategy vs another, thus ultimately providing the clinical gain in terms of time-dependent functions. Accurately assessing clinically and economic meaningful results from any intervention trial reporting positive results through this approach, facilitates objective comparisons and increases reliability in predicting survival among the various therapeutic options provided. TRIAL REGISTRATION: PROVE-IT (Pravastatin or Atorvastatin Evaluation and Infection Therapy (TIMI22), Clinical trial registration number: NCT00382460, date of registration: September 29, 2006, study start date: November 2000). LIFE (Losartan Intervention For Endpoint Reduction in Hypertension (LIFE) Study, Clinical trial registration number: NCT00338260, date of registration: June 20, 2006, study start date: June 1995). HOPE (Heart Outcomes Prevention Evaluation; we could not find Clinical trial registration number and date of registration). |
format | Online Article Text |
id | pubmed-7318394 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-73183942020-06-29 A novel method for interpreting survival analysis data: description and test on three major clinical trials on cardiovascular prevention Mengozzi, Alessandro Tricò, Domenico Natali, Andrea Trials Methodology BACKGROUND: Major results of randomized clinical trials on cardiovascular prevention are currently provided in terms of relative or absolute risk reductions, including also the number needed to treat (NNT), incorrectly implying that a treatment might prevent the occurrence of the outcome/s under investigation. Provided that these results are based on survival analysis, the primary measure of which is time-to-the outcome and not the outcome itself, we sought an alternative method to describe, analyse and interpret clinical trial results consistent with this assumption, so as to better define qualitative and quantitative heterogeneity of various therapeutic strategies in terms of their effects and costs. METHODS: The original Kaplan-Meier graphs of three major positive cardiovascular prevention trials (PROVE-IT, LIFE and HOPE) were captured from the PDF images of the article and then digitalized. We calculated the difference between the placebo and active treatment curves and plotted it as a function of time to describe the event-free time gain (Time-Gain) produced by the active treatment. By calculating the exposure to the active treatment in terms of months (MoT) as a function of time and dividing it for the corresponding time-dependent number of event-free years gained (i.e. months/12), we described the kinetics of the pharmaco-economic index MoT/y(+). The same procedure was repeated replacing MoT with the actual number of patients being treated at each time point as a function of time to obtain the NNT to gain 1 event-free year (NNT/y(+)) curve. RESULTS: The Time-Gain curves depict the kinetics of the treatment-related effect over time and possess the peculiar feature of being smooth and accurately fitted by second-order polynomial functions (a*time(2) + b*time); similarly, also the MoT/y(+) and NNT/y(+) curves can be accurately fitted by power functions (a*time(b)). These curves and indices allow to fully appreciate the quantitative and qualitative heterogeneity, both in terms of effects and costs, of the different therapeutic strategies adopted in the three trials. CONCLUSIONS: With our novel method, by exploiting original Kaplan-Meier curves from three major clinical trials on cardiovascular prevention, we generate new information on the actual consequences of choosing a therapeutic strategy vs another, thus ultimately providing the clinical gain in terms of time-dependent functions. Accurately assessing clinically and economic meaningful results from any intervention trial reporting positive results through this approach, facilitates objective comparisons and increases reliability in predicting survival among the various therapeutic options provided. TRIAL REGISTRATION: PROVE-IT (Pravastatin or Atorvastatin Evaluation and Infection Therapy (TIMI22), Clinical trial registration number: NCT00382460, date of registration: September 29, 2006, study start date: November 2000). LIFE (Losartan Intervention For Endpoint Reduction in Hypertension (LIFE) Study, Clinical trial registration number: NCT00338260, date of registration: June 20, 2006, study start date: June 1995). HOPE (Heart Outcomes Prevention Evaluation; we could not find Clinical trial registration number and date of registration). BioMed Central 2020-06-26 /pmc/articles/PMC7318394/ /pubmed/32586346 http://dx.doi.org/10.1186/s13063-020-04511-y Text en © The Author(s) 2020 Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Methodology Mengozzi, Alessandro Tricò, Domenico Natali, Andrea A novel method for interpreting survival analysis data: description and test on three major clinical trials on cardiovascular prevention |
title | A novel method for interpreting survival analysis data: description and test on three major clinical trials on cardiovascular prevention |
title_full | A novel method for interpreting survival analysis data: description and test on three major clinical trials on cardiovascular prevention |
title_fullStr | A novel method for interpreting survival analysis data: description and test on three major clinical trials on cardiovascular prevention |
title_full_unstemmed | A novel method for interpreting survival analysis data: description and test on three major clinical trials on cardiovascular prevention |
title_short | A novel method for interpreting survival analysis data: description and test on three major clinical trials on cardiovascular prevention |
title_sort | novel method for interpreting survival analysis data: description and test on three major clinical trials on cardiovascular prevention |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7318394/ https://www.ncbi.nlm.nih.gov/pubmed/32586346 http://dx.doi.org/10.1186/s13063-020-04511-y |
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