Our ability to detect these smaller cancers increased over about eight years from 25.3 per thousand to 34.7 per thousand – about a 37% improvement
In the words of the study’s author, “The change likely reflects improvements in mammography imaging technology, which permit the visualization of smaller lesions and greater detection of calcifications that result in increased cancer detection.”
The underlying assumption was that earlier detection results in a better outcome and the measure of early was size.
Therapy informed diagnosis and diagnosis responded. It wasn’t simply that size mattered, but for mammography, it was all that could be measured. Once identified, the lump biopsied, cancer confirmed and treatment initiated.
Another important treatment discovery was our failure to treat all small lumps successfully.
Categorizing lumps by size was too heterogeneous for treatment. Size does not precisely identify biologic behavior.
As best we can tell, that behavior is more closely associated with cancer’s response to hormones.
From treatment’s viewpoint, we now want to characterize cancers by their behavior; size is no longer the best measure.
With the advantage of hindsight, the authors correlated the size of breast cancer at detection with the three markers we use to measure biological behavior, the grade (increasing abnormal appearance of the cells), and the response to estrogen and progesterone.
This graph, from the study, captures the essence of their findings.
size is heterogeneous regarding behavior. Some small tumors are biologically very aggressive (unfavorable in the chart) and others not so much. And the proportion of favorable tumors increases for patients over 40, the group of patients most likely to be diagnosed with cancer.
The authors conclude, “Both tumor size and biologic features influence prognosis, but frequently a large favorable tumor can have a better prognosis than a small unfavorable tumor.
Bottom line, size has lost its primary prognostic role, challenged by grade and hormone receptor status, measures that mammography cannot identify.
All our effort in improving mammography to detect small has increased our difficulties
as “An over- diagnosed cancer is one detected by screening that would not have presented clinically during the patient’s lifetime in the absence of screening, i.e., the patient would have died from other causes with preclinical disease. …it does not matter if the tumor would eventually progress, but whether it would progress within the lifetime of the patient.”
Treatment should be tailored to the patient – there is no sense in treating a five-year problem in a patient who will die of other causes in a year. But I had always thought of that as judgment, informed by evidence.
We are over treatingbecause when stratified by biologic behavior and not size some of these tumors will take 15 years or more to become problematic.
And this begins to put breast cancer treatment into the perspective where prostate cancer has lingered for many years
Who do you treat when the tumor is slow-growing, and the life expectancy is shorter than the tumor’s growth?
Individualizing treatment algorithms is quantitative speak for clinical judgment.