I work in pediatric oncology. In layman’s terms, childhood cancer. While my job involves pipetting at a bench rather than seeing patients, I’ve become acquainted with survival curves–statistical snapshots representing how a group of patients fares over a set amount of time. These curves are often used in clinical trials to compare survival between groups receiving different treatments in order to determine if the new treatment really is more effective.

In general, estimation of survival time is not very cut and dry. An individual’s outcome isn’t necessarily going to be dictated by a statistic, just because it’s hard to accurately estimate how long someone has to live. Even doctors have a difficult time predicting survival, because what they know is based on previous patient data and their own experiences in seeing patients. While they can’t see into the future, they can do their best. Doctors do tend to be overly optimistic in their predictions. Regardless, the patient has to make a decision: start preparing for their death, or hold out hope that things will get better. A patient who has much less time to live than their doctor predicts may not be prepared for their death, but it’s pretty terrifying to face your own mortality.

That isn’t to say that you should go out and disregard everything your doctor says. Some of the problem also comes down to issues in communication. It’s a little of what we try to address in MSO: a better understanding of what they mean. When a doctor tells a patient they have x amount of time to live, it’s not to be understood as an absolute number but as a median. If that time is one year, it means that 50% of the patients at one year after diagnosis will be alive and 50% will have died. But there are a variety of factors that also come into play. In good health, you may be able to withstand treatment and live for longer. Or it may progress quickly, beyond anyone’s predictions.

Mortality estimation is not an absolute estimate but a median.

Image Source: Justin Sullivan

For example, in leukemia, there are certain indicators of good and bad prognosis. A common mutation where genes on chromosome 12 and 21 fuse is known as the ETV6/RUNX1 translocation and is associated with good prognosis–patients usually do very well. In contrast, rearrangements involving a specific gene on chromosome 11 are associated with aggressive disease and bad prognosis.

These things can only tell you how likely you are to survive, as horrible as that sounds, but it isn’t absolute. You could be in the small percentage of patients who don’t do well with a favorable prognosis, or in the low percentage of patients who are cured even with aggressive disease. With new advances in patient treatment, the hope is to extend lives and to find cures. What we can do now is to make sure patients understand what’s going on–from their diagnosis, how long they have to live, and the therapy they’re receiving–and to do all we can to help.

Feature Image Source: stefanos papachristou

Kailyn Kim

Author Kailyn Kim

Kailyn graduated from UC Berkeley with a degree in Molecular & Cell Biology. After taking time off to do research, she is currently a first year medical student on the east coast.

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