A systematic review evaluating the relationship between progression free survival and post progression survival in advanced ovarian cancer

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• 作者：Sudha Sundar^a ; ^b ; Jianhua Wu^c ; Kathryn Hillaby^a ; Jason Yap^a ; Richard Lilford^c ; ^{r.j.lilford@bham.ac.uk}
• 关键词：Progression free survival ; Post progression survival ; Overall survival ; Ovarian cancer ; Primary cancer ; Recurrent cancer
• 刊名：Gynecologic Oncology
• 出版年：2012
• 期刊代码：295_00908258
• 类别：med
• 出版时间：May, 2012
• 卷：125
• 期：2
• 页码：493-499
• 文件大小：523 K

摘要

Objective

Although overall survival is the ultimate goal of cancer therapy, many clinical and health economic decisions are taken when only progression free survival (PFS) data are available. This study evaluates the relationship between PFS and post progression survival (i.e. the time between disease progression and death) to estimate how many months a new drug for ovarian cancer might add to overall survival if the number of months the drug added to PFS (relative to a standard drug) was already known.

Methods

A literature search was conducted over Medline for randomised controlled trials published between January 1990 and July 2010 that evaluated the effect of a drug treatment in comparison to alternative drug treatment in patients with either advanced stage primary or recurrent ovarian cancer. A systematic review of progression free and post progression survival (PPS) was performed. The relationship between PFS and PPS was evaluated by a graphical method and standard statistical tests.

Results

Thirty-seven trials involving 15,850 patients met the inclusion criteria. The review found that increases in median PFS generally lead to little change in post-progression survival. Percentage gains in PFS are generally associated with no percentage gains or with very slight percentage gains or losses in post-progression survival

Conclusion

If the effect of a new drug treatment for ovarian cancer is to extend median PFS by x months, then it is reasonable to estimate that the treatment will also extend median overall survival by x months. This information will be useful for individual and collective decision making.