Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Nov 13;4(6):e000583.
doi: 10.1136/esmoopen-2019-000583. eCollection 2019.

Community-driven development of a modified progression-free survival ratio for precision oncology

Collaborators, Affiliations

Community-driven development of a modified progression-free survival ratio for precision oncology

Andreas Mock et al. ESMO Open. .

Erratum in

Abstract

Objective: Measuring the success of molecularly guided therapies is a major challenge in precision oncology trials. A commonly used endpoint is an intra-patient progression-free survival (PFS) ratio, defined as the PFS interval associated with molecularly guided therapy (PFS2) divided by the PFS interval associated with the last prior systemic therapy (PFS1), above 1.3 or, in some studies, above 1.33 or 1.5.

Methods: To investigate if the concept of PFS ratios is in agreement with actual response evaluations by physicians, we conducted a survey among members of the MASTER (Molecularly Aided Stratification for Tumor Eradication Research) Programme of the German Cancer Consortium who were asked to classify the success of molecularly guided therapies in 194 patients enrolled in the MOSCATO 01 trial based on PFS1 and PFS2 times.

Results: A comparison of classification profiles revealed three distinct clusters of PFS benefit assessments. Only 29% of assessments were consistent with a PFS ratio threshold of 1.3, whereas the remaining 71% of participants applied a different classification scheme that did not rely on the relation between PFS times alone, but also took into account absolute PFS1 intervals. Based on these community-driven insights, we developed a modified PFS ratio that incorporates the influence of absolute PFS1 intervals on the judgement of clinical benefit by physicians. Application of the modified PFS ratio to outcome data from two recent precision oncology trials, MOSCATO 01 and WINTHER, revealed significantly improved concordance with physician-perceived clinical benefit and identified comparable proportions of patients who benefited from molecularly guided therapies.

Conclusions: The modified PFS ratio may represent a meaningful clinical endpoint that could aid in the design and interpretation of future precision oncology trials.

Keywords: N-of-1 clinical trials; PFS; personalized oncology.

PubMed Disclaimer

Conflict of interest statement

Competing interests: SF has had a consulting or advisory role, received honoraria, research funding, and/or travel/accommodation expenses from the following for-profit companies: Bayer, Roche, Amgen, Eli Lilly, PharmaMar, AstraZeneca, and Pfizer.

Figures

Figure 1
Figure 1
Physician-perceived clinical benefit of molecularly guided therapy. (A) PFS1 and PFS2 times of 194 patients enrolled in the MOSCATO 01 trial. (B) Examples of response assessments by physicians based on PFS1 and PFS2 times. (C) Distribution of fraction of responder class assignments. For example, a fraction of 1 denotes that all physicians classified the respective case as responder to molecularly guided therapy. (D) Binary heatmap of response classifications (rows) by 100 physicians (columns) showing three distinct clusters of assessments (k-means clustering with k=3). Classifications were stratified by PFSr threshold. Stacked bar plots indicate the sum of response classifications (bottom). (E) Boxplots comparing the row-wise fraction of responder class assignments by physicians between the three clusters. (F) Boxplots comparing the concordance of response classifications by physicians with the class defined by a PFSr above 1.3 between the three clusters. *p<0.05, **p<0.01, ***p<0.001. PFS, progression-free survival; PFSr, PFS ratio.
Figure 2
Figure 2
Discordance between physician-perceived clinical benefit and PFSr threshold. (A) Fraction of cases classified as responders plotted over PFS2 time, coloured according to PFSr. (B) Fraction of cases classified as responders plotted over PFS2 time, coloured according to discordance between physician classification, which was considered as the ground truth, and PFSr threshold. (C) PFS2 time plotted over PFS1 time, coloured according to discordance between physician classification and PFSr threshold. (D) PFSr plotted over PFS2 (top) and PFS1 (bottom), coloured according to discordance between physician classification and PFSr threshold. PFS, progression-free survival; PFSr, PFS ratio.
Figure 3
Figure 3
Definition of a mPFSr. (A) Algebraic definition of a mPFSr. In contrast to standard PFSr, the PFS2 interval is divided by the so-called prePFS time to correct for false positive predictions. In addition, PFS2 times above 6 months are set to 24 months to correct for false negatives (postPFS). (B) Boxplots comparing the concordance with the physician classification between PFSr and mPFSr. *p<0.05, **p<0.01, ***p<0.001. (C, D) Alluvial diagrams comparing the classification of patients from the MOSCATO 01 (C) and WINTHER (D) trials according to PFSr and mPFSr thresholds of 1.3. mPFSr, modified PFSr; PFS, progression-free survival; PFSr, PFS ratio.

References

    1. Subbiah V, Kurzrock R. Challenging standard-of-care paradigms in the precision oncology era. Trends Cancer 2018;4:101–9. 10.1016/j.trecan.2017.12.004 - DOI - PMC - PubMed
    1. Cherny NI, de Vries EGE, Dafni U, et al. . Comparative assessment of clinical benefit using the ESMO-magnitude of clinical benefit scale version 1.1 and the ASCO value framework net health benefit score. J Clin Oncol 2019;37:336–49. 10.1200/JCO.18.00729 - DOI - PubMed
    1. Driscoll JJ, Rixe O. Overall survival: still the gold standard. Cancer J 2009;15:401–5. 10.1097/PPO.0b013e3181bdc2e0 - DOI - PubMed
    1. Moscow JA, Fojo T, Schilsky RL. The evidence framework for precision cancer medicine. Nat Rev Clin Oncol 2018;15:183–92. 10.1038/nrclinonc.2017.186 - DOI - PubMed
    1. Von Hoff DD, Stephenson JJ, Rosen P, et al. . Pilot study using molecular profiling of patients' tumors to find potential targets and select treatments for their refractory cancers. J Clin Oncol 2010;28:4877–83. 10.1200/JCO.2009.26.5983 - DOI - PubMed

Publication types

MeSH terms

LinkOut - more resources