Survival rates for those with later-stage cancer are progressively increasing with better treatment and earlier diagnosis; however, one of the first questions often still asked by the patient is “how long have I got?” It is therefore important that not only is this answer clearly and compassionately delivered to the patient, but also that it is accurate.
Research from Dr Belinda Kiely, a cancer specialist at the University of Sydney, Sydney, Australia, suggests that only 20–30% of the survival rate estimates are correct. This troubling figure does not only show that patients are given false positivity/negativity around their diagnosis, but that a majority of patients are not provided with a useful timeline of their remaining life.
To determine the best approach in advising patients on their estimated survival, Dr Kiely worked with 33 cancer specialists who advised 146 breast cancer patients about their estimated survival time. Normally, a single number estimate is given to the patient, and is rarely accurate and gives no indication of a longer possible survival time. Dr Kiely believes it to be beneficial to provide three different, case-specific estimates. This method helps calculate the patient’s individual best, worst, and typical survival time. The estimated survival time is divided by four to determine the worst-case scenario and multiply it by three for the best case.
This approach should fulfil the patient’s wishes to receive an estimation that is realistic to allow appropriate planning of healthcare and their remaining life. Of the 146 patients who took part, 91% found the three-scenario method useful. Furthermore, 88% commented that they were informed enough to plan for the future because of a better understanding of their possible outcomes, and 77% reported that this approach was equal to or more optimistic and reassuring than they had expected.
“Providing patients with a single number estimate of the average survival time is rarely accurate and conveys no hope of a possible longer survival time. Instead, we have devised a method that helps doctors calculate the best case, worst case, and typical survival times for individual patients,” commented Dr Kiely.
