Abstract
Objective: The purpose of this paper is to highlight and solve an issue of importance that affects the well-being and confidence of cancer sufferers world-wide.
Design: It is well documented that there may be a relatively high risk, once a patient achieves remission, of the cancer returning and this is a question in the forefront of every patient's mind. This risk of relapse may depend on the attributes (gender, age, well-being) of the patient, although there is general agreement that, if the cancer does return, it will almost certainly be within a given number of months or years. The aim is to produce an effective way of updating a patient on the chance they will relapse.
Materials and Methods: Two models are considered, including a stepwise Kaplan-Meier type, that enable a doctor to provide a better estimate to the patient of the chance of a relapse as time passes since remission. These are conditional probability models based on the best information known.
Results: A combined model is found to be appropriate and suitable equations for calculating the relevant conditional probabilities are derived. A simple table illustrating the technique is also provided.
Conclusion: It is possible to give cancer sufferers in all countries better information on the likelihood that they will relapse, given that they have survived to a certain point. This provides an uplifting experience and an increase in confidence.
Design: It is well documented that there may be a relatively high risk, once a patient achieves remission, of the cancer returning and this is a question in the forefront of every patient's mind. This risk of relapse may depend on the attributes (gender, age, well-being) of the patient, although there is general agreement that, if the cancer does return, it will almost certainly be within a given number of months or years. The aim is to produce an effective way of updating a patient on the chance they will relapse.
Materials and Methods: Two models are considered, including a stepwise Kaplan-Meier type, that enable a doctor to provide a better estimate to the patient of the chance of a relapse as time passes since remission. These are conditional probability models based on the best information known.
Results: A combined model is found to be appropriate and suitable equations for calculating the relevant conditional probabilities are derived. A simple table illustrating the technique is also provided.
Conclusion: It is possible to give cancer sufferers in all countries better information on the likelihood that they will relapse, given that they have survived to a certain point. This provides an uplifting experience and an increase in confidence.
| Original language | English |
|---|---|
| Pages (from-to) | 95-98 |
| Number of pages | 4 |
| Journal | International Medical Journal |
| Volume | 25 |
| Issue number | 2 |
| Publication status | Published - Apr 2018 |
Keywords
- cancer
- relapse
- conditional probability
- Kaplan-Meier
- statistical models