Cargando…
Estimating Systolic Blood Pressure Intervention Trial Participant Posttrial Survival Using Pooled Epidemiologic Cohort Data
BACKGROUND: Intensive systolic blood pressure treatment (<120 mm Hg) in SPRINT (Systolic Blood Pressure Intervention Trial) improved survival compared with standard treatment (<140 mm Hg) over a median follow‐up of 3.3 years. We projected life expectancy after observed follow‐up in SPRINT usin...
Autores principales: | , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8200698/ https://www.ncbi.nlm.nih.gov/pubmed/33955229 http://dx.doi.org/10.1161/JAHA.120.020361 |
_version_ | 1783707661503561728 |
---|---|
author | Bellows, Brandon K. Zhang, Yiyi Zhang, Zugui Lloyd‐Jones, Donald M. Bress, Adam P. King, Jordan B. Kolm, Paul Cushman, William C. Johnson, Karen C. Tamariz, Leonardo Oelsner, Elizabeth C. Shea, Steven Newman, Anne B. Ives, Diane G. Couper, David Moran, Andrew E. Weintraub, William S. |
author_facet | Bellows, Brandon K. Zhang, Yiyi Zhang, Zugui Lloyd‐Jones, Donald M. Bress, Adam P. King, Jordan B. Kolm, Paul Cushman, William C. Johnson, Karen C. Tamariz, Leonardo Oelsner, Elizabeth C. Shea, Steven Newman, Anne B. Ives, Diane G. Couper, David Moran, Andrew E. Weintraub, William S. |
author_sort | Bellows, Brandon K. |
collection | PubMed |
description | BACKGROUND: Intensive systolic blood pressure treatment (<120 mm Hg) in SPRINT (Systolic Blood Pressure Intervention Trial) improved survival compared with standard treatment (<140 mm Hg) over a median follow‐up of 3.3 years. We projected life expectancy after observed follow‐up in SPRINT using SPRINT‐eligible participants in the NHLBI‐PCS (National Heart, Lung, and Blood Institute Pooled Cohorts Study). METHODS AND RESULTS: We used propensity scores to weight SPRINT‐eligible NHLBI‐PCS participants to resemble SPRINT participants. In SPRINT participants, we estimated in‐trial survival (<4 years) using a time‐based flexible parametric survival model. In SPRINT‐eligible NHLBI‐PCS participants, we estimated posttrial survival (≥4 years) using an age‐based flexible parametric survival model and applied the formula to SPRINT participants to predict posttrial survival. We projected overall life expectancy for each SPRINT participant and compared it to parametric regression (eg, Gompertz) projections based on SPRINT data alone. We included 8584 SPRINT and 10 593 SPRINT‐eligible NHLBI‐PCS participants. After propensity weighting, mean (SD) age was 67.9 (9.4) and 68.2 (8.8) years, and 35.5% and 37.6% were women in SPRINT and NHLBI‐PCS, respectively. Using the NHLBI‐PCS–based method, projected mean life expectancy from randomization was 21.0 (7.4) years with intensive and 19.1 (7.2) years with standard treatment. Using the Gompertz regression, life expectancy was 11.2 (2.3) years with intensive and 10.5 (2.2) years with standard treatment. CONCLUSIONS: Combining SPRINT and NHLBI‐PCS observed data likely offers a more realistic estimate of life expectancy than parametrically extrapolating SPRINT data alone. These results offer insight into the potential long‐term effectiveness of intensive SBP goals. |
format | Online Article Text |
id | pubmed-8200698 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82006982021-06-15 Estimating Systolic Blood Pressure Intervention Trial Participant Posttrial Survival Using Pooled Epidemiologic Cohort Data Bellows, Brandon K. Zhang, Yiyi Zhang, Zugui Lloyd‐Jones, Donald M. Bress, Adam P. King, Jordan B. Kolm, Paul Cushman, William C. Johnson, Karen C. Tamariz, Leonardo Oelsner, Elizabeth C. Shea, Steven Newman, Anne B. Ives, Diane G. Couper, David Moran, Andrew E. Weintraub, William S. J Am Heart Assoc Original Research BACKGROUND: Intensive systolic blood pressure treatment (<120 mm Hg) in SPRINT (Systolic Blood Pressure Intervention Trial) improved survival compared with standard treatment (<140 mm Hg) over a median follow‐up of 3.3 years. We projected life expectancy after observed follow‐up in SPRINT using SPRINT‐eligible participants in the NHLBI‐PCS (National Heart, Lung, and Blood Institute Pooled Cohorts Study). METHODS AND RESULTS: We used propensity scores to weight SPRINT‐eligible NHLBI‐PCS participants to resemble SPRINT participants. In SPRINT participants, we estimated in‐trial survival (<4 years) using a time‐based flexible parametric survival model. In SPRINT‐eligible NHLBI‐PCS participants, we estimated posttrial survival (≥4 years) using an age‐based flexible parametric survival model and applied the formula to SPRINT participants to predict posttrial survival. We projected overall life expectancy for each SPRINT participant and compared it to parametric regression (eg, Gompertz) projections based on SPRINT data alone. We included 8584 SPRINT and 10 593 SPRINT‐eligible NHLBI‐PCS participants. After propensity weighting, mean (SD) age was 67.9 (9.4) and 68.2 (8.8) years, and 35.5% and 37.6% were women in SPRINT and NHLBI‐PCS, respectively. Using the NHLBI‐PCS–based method, projected mean life expectancy from randomization was 21.0 (7.4) years with intensive and 19.1 (7.2) years with standard treatment. Using the Gompertz regression, life expectancy was 11.2 (2.3) years with intensive and 10.5 (2.2) years with standard treatment. CONCLUSIONS: Combining SPRINT and NHLBI‐PCS observed data likely offers a more realistic estimate of life expectancy than parametrically extrapolating SPRINT data alone. These results offer insight into the potential long‐term effectiveness of intensive SBP goals. John Wiley and Sons Inc. 2021-05-06 /pmc/articles/PMC8200698/ /pubmed/33955229 http://dx.doi.org/10.1161/JAHA.120.020361 Text en © 2021 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Original Research Bellows, Brandon K. Zhang, Yiyi Zhang, Zugui Lloyd‐Jones, Donald M. Bress, Adam P. King, Jordan B. Kolm, Paul Cushman, William C. Johnson, Karen C. Tamariz, Leonardo Oelsner, Elizabeth C. Shea, Steven Newman, Anne B. Ives, Diane G. Couper, David Moran, Andrew E. Weintraub, William S. Estimating Systolic Blood Pressure Intervention Trial Participant Posttrial Survival Using Pooled Epidemiologic Cohort Data |
title | Estimating Systolic Blood Pressure Intervention Trial Participant Posttrial Survival Using Pooled Epidemiologic Cohort Data |
title_full | Estimating Systolic Blood Pressure Intervention Trial Participant Posttrial Survival Using Pooled Epidemiologic Cohort Data |
title_fullStr | Estimating Systolic Blood Pressure Intervention Trial Participant Posttrial Survival Using Pooled Epidemiologic Cohort Data |
title_full_unstemmed | Estimating Systolic Blood Pressure Intervention Trial Participant Posttrial Survival Using Pooled Epidemiologic Cohort Data |
title_short | Estimating Systolic Blood Pressure Intervention Trial Participant Posttrial Survival Using Pooled Epidemiologic Cohort Data |
title_sort | estimating systolic blood pressure intervention trial participant posttrial survival using pooled epidemiologic cohort data |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8200698/ https://www.ncbi.nlm.nih.gov/pubmed/33955229 http://dx.doi.org/10.1161/JAHA.120.020361 |
work_keys_str_mv | AT bellowsbrandonk estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata AT zhangyiyi estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata AT zhangzugui estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata AT lloydjonesdonaldm estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata AT bressadamp estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata AT kingjordanb estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata AT kolmpaul estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata AT cushmanwilliamc estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata AT johnsonkarenc estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata AT tamarizleonardo estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata AT oelsnerelizabethc estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata AT sheasteven estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata AT newmananneb estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata AT ivesdianeg estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata AT couperdavid estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata AT moranandrewe estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata AT weintraubwilliams estimatingsystolicbloodpressureinterventiontrialparticipantposttrialsurvivalusingpooledepidemiologiccohortdata |