DynNom Survival — User Guide

              

              
1. Page Structure

              
This app contains 5 tabs. Use the left panel for settings and the right panel for results:

              
    
                
  • 
                  Data Preview
                   — View the loaded data table (time, event, covariates)
                
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  • 
                  Nomogram
                   — Display the Cox proportional hazards model nomogram
                
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  • 
                  Model Summary
                   — Model summary with coefficients, HR, and P-values
                
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  • 
                  Prediction
                   — Enter patient variable values to predict survival probabilities
                
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  • 
                  Help
                   — This page
                
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2. Workflow

              
    
                
  1. Select a data source (Demo Lung data or upload CSV/XLSX) on the left and click 'Load Data'
    2. 
                
  2. Select the time variable, event variable, and covariates (at least 2)
    3. 
                
  3. Set survival time evaluation points (default: 25%, 50%, 75% quantiles)
    4. 
                
  4. Click 'Run Analysis' to build the Cox model
    5. 
                
  5. Switch to the 'Prediction' tab and enter patient variable values
    6. 
                
  6. Click 'Predict' to view survival probabilities at each time point with nomogram annotation
    7. 
              

              
3. Prediction Details

              
In the Prediction tab:

              
    
                
  • Enter values for each covariate (numeric or categorical)
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  • Supports custom evaluation time points, separated by commas or semicolons (e.g. 6,12,24,36)
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  • Results include: variable points, total points, linear predictor, and survival probability at each time point
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  • The nomogram on the right uses red arrows to mark the current patient's position
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4. Data Format Requirements

              
    
                
  • 
                  Time variable (time):
                  Numeric, representing follow-up time (months)
                
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  • 
                  Event variable (event):
                  0/1 or TRUE/FALSE, 1 means event occurred (death)
                
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  • 
                  Covariates:
                  Numeric or categorical, at least 2 required
                
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  • Missing values will be automatically removed
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5. Model Principle

              
This app is based on the Cox proportional hazards model:

              
h(t|X) = h₀(t) × exp(β₁X₁ + β₂X₂ + ... + βₖXₖ)

              
Where h₀(t) is the baseline hazard and exp(βX) is the hazard ratio (HR).

              
The nomogram maps the Cox model's linear predictor to Points, then reads survival probabilities at each time point from the Total Points.

              

              

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