Impact of disease progression date determination on progression-free survival estimates in advanced lung cancer

Yingwei Qi, Katie L. Allen Ziegler, Shauna L. Hillman, Mary W. Redman, Steven E. Schild, David R. Gandara, Alex Adjei, Sumithra J. Mandrekars

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Background: In patients with advanced lung cancer, overall survival is largely influenced by progression status. Because progression-free survival (PFS)-based endpoints are controversial, the authors evaluated the impact of the progression date (PD) determination approach on PFS estimates. Methods: Individual patient data from 21 trials (14 North Central Cancer Treatment Group trials and 7 Southwest Oncology Group trials) were used. The reported PD (RPD) was defined as either the radiographic scan date or the clinical deterioration date. PD was determined using Method 1 (M1), the RPD; M2, 1 day after the last progression-free scan; M3, midpoint between the last progression-free scan and the RPD; and M4, an interval-censoring approach. PFS was estimated using Kaplan-Meier (M1-M3), and maximum-likelihood (M4) methods. Simulation studies were performed to understand the impact of the length of time elapsed between the last progression-free scan and the PD on time-to-progression estimates. Results: PFS estimates using the RPD were the highest, and M2 was the most conservative. M3 and M4 were similar because the majority of progressions occurred during treatment (ie, frequent disease assessments). M3 was influenced less by the length of the assessment schedules (percentage difference from the true time-to-progression, <1.5%) compared with M1 (11% to 30%) and M2 (-8% to -29%). The overall study conclusion was unaffected by the method used for randomized trials. Conclusions: The magnitude of difference in the PFS estimates was large enough to alter trial conclusions in patients with advanced lung cancer. The results indicate that standards for PD determination, the use of sensitivity analyses, and randomized trials are critical when designing trials and reporting efficacy using PFS-based endpoints. Cancer 2012.

Original languageEnglish (US)
Pages (from-to)5358-5365
Number of pages8
JournalCancer
Volume118
Issue number21
DOIs
StatePublished - Nov 1 2012

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Disease-Free Survival
Disease Progression
Lung Neoplasms
Neoplasms
Appointments and Schedules
Survival
Therapeutics

Keywords

  • advanced lung cancer
  • clinical trials
  • disease progression date
  • progression-free survival
  • tumor assessment schedule

ASJC Scopus subject areas

  • Cancer Research
  • Oncology

Cite this

Qi, Y., Allen Ziegler, K. L., Hillman, S. L., Redman, M. W., Schild, S. E., Gandara, D. R., ... Mandrekars, S. J. (2012). Impact of disease progression date determination on progression-free survival estimates in advanced lung cancer. Cancer, 118(21), 5358-5365. https://doi.org/10.1002/cncr.27528

Impact of disease progression date determination on progression-free survival estimates in advanced lung cancer. / Qi, Yingwei; Allen Ziegler, Katie L.; Hillman, Shauna L.; Redman, Mary W.; Schild, Steven E.; Gandara, David R.; Adjei, Alex; Mandrekars, Sumithra J.

In: Cancer, Vol. 118, No. 21, 01.11.2012, p. 5358-5365.

Research output: Contribution to journalArticle

Qi, Y, Allen Ziegler, KL, Hillman, SL, Redman, MW, Schild, SE, Gandara, DR, Adjei, A & Mandrekars, SJ 2012, 'Impact of disease progression date determination on progression-free survival estimates in advanced lung cancer', Cancer, vol. 118, no. 21, pp. 5358-5365. https://doi.org/10.1002/cncr.27528
Qi Y, Allen Ziegler KL, Hillman SL, Redman MW, Schild SE, Gandara DR et al. Impact of disease progression date determination on progression-free survival estimates in advanced lung cancer. Cancer. 2012 Nov 1;118(21):5358-5365. https://doi.org/10.1002/cncr.27528
Qi, Yingwei ; Allen Ziegler, Katie L. ; Hillman, Shauna L. ; Redman, Mary W. ; Schild, Steven E. ; Gandara, David R. ; Adjei, Alex ; Mandrekars, Sumithra J. / Impact of disease progression date determination on progression-free survival estimates in advanced lung cancer. In: Cancer. 2012 ; Vol. 118, No. 21. pp. 5358-5365.
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abstract = "Background: In patients with advanced lung cancer, overall survival is largely influenced by progression status. Because progression-free survival (PFS)-based endpoints are controversial, the authors evaluated the impact of the progression date (PD) determination approach on PFS estimates. Methods: Individual patient data from 21 trials (14 North Central Cancer Treatment Group trials and 7 Southwest Oncology Group trials) were used. The reported PD (RPD) was defined as either the radiographic scan date or the clinical deterioration date. PD was determined using Method 1 (M1), the RPD; M2, 1 day after the last progression-free scan; M3, midpoint between the last progression-free scan and the RPD; and M4, an interval-censoring approach. PFS was estimated using Kaplan-Meier (M1-M3), and maximum-likelihood (M4) methods. Simulation studies were performed to understand the impact of the length of time elapsed between the last progression-free scan and the PD on time-to-progression estimates. Results: PFS estimates using the RPD were the highest, and M2 was the most conservative. M3 and M4 were similar because the majority of progressions occurred during treatment (ie, frequent disease assessments). M3 was influenced less by the length of the assessment schedules (percentage difference from the true time-to-progression, <1.5{\%}) compared with M1 (11{\%} to 30{\%}) and M2 (-8{\%} to -29{\%}). The overall study conclusion was unaffected by the method used for randomized trials. Conclusions: The magnitude of difference in the PFS estimates was large enough to alter trial conclusions in patients with advanced lung cancer. The results indicate that standards for PD determination, the use of sensitivity analyses, and randomized trials are critical when designing trials and reporting efficacy using PFS-based endpoints. Cancer 2012.",
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AB - Background: In patients with advanced lung cancer, overall survival is largely influenced by progression status. Because progression-free survival (PFS)-based endpoints are controversial, the authors evaluated the impact of the progression date (PD) determination approach on PFS estimates. Methods: Individual patient data from 21 trials (14 North Central Cancer Treatment Group trials and 7 Southwest Oncology Group trials) were used. The reported PD (RPD) was defined as either the radiographic scan date or the clinical deterioration date. PD was determined using Method 1 (M1), the RPD; M2, 1 day after the last progression-free scan; M3, midpoint between the last progression-free scan and the RPD; and M4, an interval-censoring approach. PFS was estimated using Kaplan-Meier (M1-M3), and maximum-likelihood (M4) methods. Simulation studies were performed to understand the impact of the length of time elapsed between the last progression-free scan and the PD on time-to-progression estimates. Results: PFS estimates using the RPD were the highest, and M2 was the most conservative. M3 and M4 were similar because the majority of progressions occurred during treatment (ie, frequent disease assessments). M3 was influenced less by the length of the assessment schedules (percentage difference from the true time-to-progression, <1.5%) compared with M1 (11% to 30%) and M2 (-8% to -29%). The overall study conclusion was unaffected by the method used for randomized trials. Conclusions: The magnitude of difference in the PFS estimates was large enough to alter trial conclusions in patients with advanced lung cancer. The results indicate that standards for PD determination, the use of sensitivity analyses, and randomized trials are critical when designing trials and reporting efficacy using PFS-based endpoints. Cancer 2012.

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