Estimating Hazard Ratio (HR) and Confidence Interval from Survival Curves

Requirements for the KM Curve:

  • Multiple Groups: The KM curve should show the survival outcomes for at least two different groups (e.g., treatment vs. control).
  • Provide the "Number at risk" information. This shows the number of individuals at risk of the outcome at different follow-up time points.
  • Alternatively, provide the total number of individuals in each group.

Procedure:

  • When downloading literature, save the original PDF format if possible. Take screenshots of the survival curves from the literature, ensuring the images are of sufficient clarity.
  • If the saved image lacks clarity, import it into Adobe Photoshop for adjustments such as desaturation, sharpening, and adjusting the tone curve.

1. Selection of point extraction software.
Engauge Digitizer Recommend

A Comparison of Graph Digitization Software for the Reconstruction of Published Kaplan Meier Curves

In 2024, a novel algorithm streamlines the digitization process and requires minimal user input, it can be assessed here.


2. Using Engauge Digitizer as an Exanple

Online Tool Developed by Yanhong Zhou et al.
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Required Files:

  • Survival curve data in CSV format.Special Note: It is recommended to use simple labels like A and B for group variables rather than special characters to avoid connection errors on the website.
  • Scenario 1: Number at risk data for each group and corresponding time (high precision).
  • Scenario 2: Total number of individuals in each group (low precision).
  • Optional Parameter: Number of events occurring in each group.

Reconstrunction tools:

Auxiliary tool for online tool abov:.

log(HR)
Standard error
Confidence level

Reference:

[1] Liu, N., Zhou, Y. & Lee, J.J. IPDfromKM: reconstruct individual patient data from published KaplanMeier survival curves. BMC Med Res Methodol 21, 111 (2021).
[2] Zhang, J.Z., Rios, J.D., Pechlivanoglou, T. et al. SurvdigitizeR: an algorithm for automated survival curve digitization. BMC Med Res Methodol 24, 147 (2024). https://doi.org/10.1186/s12874-024-02273-8