How Long Have I Had My Cancer, Doctor?
“How long have I had this cancer, Doctor?” This is a question that patients frequently ask their oncologist.
To estimate the “age” of cancers at the time of diagnosis, we reviewed data on the “time to local/regional recurrence” (LRF) following initial surgical resection for three common cancers, then applied a modified version of Collins’ law. We conducted a systematic review of English medical literature to identify studies reporting LRF rates, over time, following surgery alone for breast, lung, or colorectal cancer. Patients who received radiation/hormones/chemotherapy were excluded since these therapies may alter tumor growth kinetics after surgery. For each disease, data were considered in three ways: 1) absolute cumulative LRF rate over time; 2) percentage of LRFs manifest over time (to facilitate comparisons between studies with different absolute magnitudes of LRFs); and 3) weighted average of the percentage of LRFs manifest over time.
For breast cancer (based on data from 3,043 patients from 5 studies), we found that the median time to LRF was 2.7 years. For lung cancer (based on data from 1,190 patients from 4 studies), the median time to LRF was 1.5 years. For rectal cancer (based on data from 3,334 patients from 10 studies), the median time to LRF was 1.5 years. Based on Collins’ law, the distribution of time to LRF suggests that the age of most of the solid tumors studied was 3 to 6 years.
“How long have I had this cancer, Doctor?” This is a question that patients frequently ask their oncologist. In many instances, the answer to the question is not particularly relevant since treatment approaches may not be influenced by the “age” of the cancer. However, in some instances the age of a cancer, which implies its natural history, may influence treatment recommendations.
In addition, the answer to this question may have helpful implications for our patients. When patients are diagnosed with cancer, they often seek to understand “why.” They search for particular events in their lives that may have “caused” the cancer to form. A better understanding of the likely age of their cancer may address misconceptions about the “causes” of their cancer and help to alleviate associated guilt (eg, “Did I cause my cancer by working too hard last month?” “No, because the cancer started to grow at least 2 years ago.”).[1-4] Also, some understanding of their cancer’s age may help to alleviate patients’ concerns regarding any delays in treatment (ie, they will be less concerned about a modest delay if they understand that the tumor has been present for a long time).
In 1955, Collins et al attempted to develop a method of measuring the growth rate of tumors. They hypothesized that if the change in tumor volume were known for a given time interval, the average growth rate could be calculated and used to estimate the time of inception for a given tumor[5]. Collins studied the interval between surgery and recurrence in patients with Wilms tumor. In a graph (see Appendix) that compared the patients’ age at diagnosis to their age at follow up, he noted that all local recurrences occurred at time intervals that were shorter than the patients’ “gestational age” (ie, their age plus 9 months) at diagnosis. This is consistent with the fact that the tumor’s “maximum age” at the time of diagnosis could be no greater than the child’s age plus 9 months. Thus, a patient whose tumor is resected at the age of 3 can be considered cured when he or she reaches the age of 6 years and 9 months. This concept, known as the period of risk for recurrence, later became known as Collins’ law.[6] Other investigators have confirmed the accuracy of Collins’ law in patients with medulloblastoma and Wilms tumor.[6-10]
To address the question “how long have I had my cancer?” we used a modified version of Collins’ law. We reviewed the reported pace of local relapse following definitive local therapy as a means of estimating the age of the initial tumor at diagnosis. We hypothesize that the time of inception for various tumors might be estimated by quantifying the interval between gross total resection and time to local failure.