New methods for estimating follow-up rates in cohort studies

Abstract Background The follow-up rate, a standard index of the completeness of follow-up, is important for assessing the validity of a cohort study. A common method for estimating the follow-up rate, the “Percentage Method”, defined as the fraction of all enrollees who developed the event of intere...

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Main Authors: Xiaonan Xue, Ilir Agalliu, Mimi Y. Kim, Tao Wang, Juan Lin, Reza Ghavamian, Howard D. Strickler
Format: Article
Language:English
Published: BMC 2017-12-01
Series:BMC Medical Research Methodology
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12874-017-0436-z
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spelling doaj-edeeea3273e24ac4821aa0495e5e1a5c2020-11-25T02:52:26ZengBMCBMC Medical Research Methodology1471-22882017-12-0117111010.1186/s12874-017-0436-zNew methods for estimating follow-up rates in cohort studiesXiaonan Xue0Ilir Agalliu1Mimi Y. Kim2Tao Wang3Juan Lin4Reza Ghavamian5Howard D. Strickler6Department of Epidemiology & Population Health, Albert Einstein College of MedicineDepartment of Epidemiology & Population Health, Albert Einstein College of MedicineDepartment of Epidemiology & Population Health, Albert Einstein College of MedicineDepartment of Epidemiology & Population Health, Albert Einstein College of MedicineDepartment of Epidemiology & Population Health, Albert Einstein College of MedicineDepartment of Urology, Albert Einstein College of Medicine and Montefiore Medical CenterDepartment of Epidemiology & Population Health, Albert Einstein College of MedicineAbstract Background The follow-up rate, a standard index of the completeness of follow-up, is important for assessing the validity of a cohort study. A common method for estimating the follow-up rate, the “Percentage Method”, defined as the fraction of all enrollees who developed the event of interest or had complete follow-up, can severely underestimate the degree of follow-up. Alternatively, the median follow-up time does not indicate the completeness of follow-up, and the reverse Kaplan-Meier based method and Clark’s Completeness Index (CCI) also have limitations. Methods We propose a new definition for the follow-up rate, the Person-Time Follow-up Rate (PTFR), which is the observed person-time divided by total person-time assuming no dropouts. The PTFR cannot be calculated directly since the event times for dropouts are not observed. Therefore, two estimation methods are proposed: a formal person-time method (FPT) in which the expected total follow-up time is calculated using the event rate estimated from the observed data, and a simplified person-time method (SPT) that avoids estimation of the event rate by assigning full follow-up time to all events. Simulations were conducted to measure the accuracy of each method, and each method was applied to a prostate cancer recurrence study dataset. Results Simulation results showed that the FPT has the highest accuracy overall. In most situations, the computationally simpler SPT and CCI methods are only slightly biased. When applied to a retrospective cohort study of cancer recurrence, the FPT, CCI and SPT showed substantially greater 5-year follow-up than the Percentage Method (92%, 92% and 93% vs 68%). Conclusions The Person-time methods correct a systematic error in the standard Percentage Method for calculating follow-up rates. The easy to use SPT and CCI methods can be used in tandem to obtain an accurate and tight interval for PTFR. However, the FPT is recommended when event rates and dropout rates are high.http://link.springer.com/article/10.1186/s12874-017-0436-zPerson-timeLoss to follow-upMedian survival timeReverse Kaplan-Meier survival curveCompeting risk
collection DOAJ
language English
format Article
sources DOAJ
author Xiaonan Xue
Ilir Agalliu
Mimi Y. Kim
Tao Wang
Juan Lin
Reza Ghavamian
Howard D. Strickler
spellingShingle Xiaonan Xue
Ilir Agalliu
Mimi Y. Kim
Tao Wang
Juan Lin
Reza Ghavamian
Howard D. Strickler
New methods for estimating follow-up rates in cohort studies
BMC Medical Research Methodology
Person-time
Loss to follow-up
Median survival time
Reverse Kaplan-Meier survival curve
Competing risk
author_facet Xiaonan Xue
Ilir Agalliu
Mimi Y. Kim
Tao Wang
Juan Lin
Reza Ghavamian
Howard D. Strickler
author_sort Xiaonan Xue
title New methods for estimating follow-up rates in cohort studies
title_short New methods for estimating follow-up rates in cohort studies
title_full New methods for estimating follow-up rates in cohort studies
title_fullStr New methods for estimating follow-up rates in cohort studies
title_full_unstemmed New methods for estimating follow-up rates in cohort studies
title_sort new methods for estimating follow-up rates in cohort studies
publisher BMC
series BMC Medical Research Methodology
issn 1471-2288
publishDate 2017-12-01
description Abstract Background The follow-up rate, a standard index of the completeness of follow-up, is important for assessing the validity of a cohort study. A common method for estimating the follow-up rate, the “Percentage Method”, defined as the fraction of all enrollees who developed the event of interest or had complete follow-up, can severely underestimate the degree of follow-up. Alternatively, the median follow-up time does not indicate the completeness of follow-up, and the reverse Kaplan-Meier based method and Clark’s Completeness Index (CCI) also have limitations. Methods We propose a new definition for the follow-up rate, the Person-Time Follow-up Rate (PTFR), which is the observed person-time divided by total person-time assuming no dropouts. The PTFR cannot be calculated directly since the event times for dropouts are not observed. Therefore, two estimation methods are proposed: a formal person-time method (FPT) in which the expected total follow-up time is calculated using the event rate estimated from the observed data, and a simplified person-time method (SPT) that avoids estimation of the event rate by assigning full follow-up time to all events. Simulations were conducted to measure the accuracy of each method, and each method was applied to a prostate cancer recurrence study dataset. Results Simulation results showed that the FPT has the highest accuracy overall. In most situations, the computationally simpler SPT and CCI methods are only slightly biased. When applied to a retrospective cohort study of cancer recurrence, the FPT, CCI and SPT showed substantially greater 5-year follow-up than the Percentage Method (92%, 92% and 93% vs 68%). Conclusions The Person-time methods correct a systematic error in the standard Percentage Method for calculating follow-up rates. The easy to use SPT and CCI methods can be used in tandem to obtain an accurate and tight interval for PTFR. However, the FPT is recommended when event rates and dropout rates are high.
topic Person-time
Loss to follow-up
Median survival time
Reverse Kaplan-Meier survival curve
Competing risk
url http://link.springer.com/article/10.1186/s12874-017-0436-z
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