Experts in the field of kidney cancer discuss the risk stratification process for renal cell carcinoma and its effect on prognosis.
Chandler H. Park, M.D.: Just to go back and talk about some of the statistics of renal cell kidney cancer, patients’ diagnosis, prognosis and so on. One of the things that we have to think about is something called the five-year survival. This is published by SEER [the Surveillance, Epidemiology, and End Results] program that provides cancer statistics. The five-year relative survival, which means al-comers, everybody that’s diagnosed with kidney cancer, it’s 77%. So that’s part of your survival. Now, what about the number of new cases? [In the United States,] 80,000 to 82,000 people are diagnosed with kidney cancer, which is about 4% to 5% of all cancers. Now, what about deaths? On average, about 14,000 to 15,000 people, unfortunately, pass away from kidney cancer every year.
How do you stratify people into different groups? As a cancer doctor, we use something called stages. It essentially boils down to people wanting to know how bad their cancer is. So I tell my patients stage 1, stage 2, stage 3 and stage 4. The way we describe stage 1 is if the cancer inside the kidney is less than 7 centimeters. So it’s strictly a size criterion. If the cancer is greater than 7 centimeters, it’s stage 2. Stage 3 is if the cancer spreads. The kidneys have a lining around them. The example I give to my patients is if I put my hand in a glove and the glove covers up my hand; a kidney also has a lining around it, just like a glove around my hand. So if the roots of the kidney cancer spread into the lining, they call it a fat pad or adipose tissue or into the blood vessels; that’s considered stage 3. Stage 4 is if the cancer cells jump into blood vessels, go into the blood and spread to the lung, liver or bone. So that’s how we determine the different stages.
In terms of cure, [it] is technically here in 2023 for stage 4 kidney cancer; some of the patients I’ve had scans for stage 4, and all the cancers disappeared. So I’ve seen patients [who are] in remission. I’m not sure if we want to use the word “cure” because we still want to keep an eye on the patients. But typically that’s how we determine prognosis, and that’s with the five-year survival. Now, how does the local and distant metastasis impact the patient’s prognosis? If it’s distant metastatic disease, that means that there tends to be cancer in other places. … [We use] that example of a seed. It takes millions of cancer seeds to come together to form 1 centimeter. So on a CT scan or an MRI, if you see a 1-centimeter lesion, that tends to be millions of cancer cells stuck together. Therefore, chances are there’s microscopic cancer somewhere. Now, what’s the risk of recurrence? Depends on whether you get a treatment or not. And we’re going to talk about some of the clinical trials. There are different risks of recurrence based on the treatment. And that has to do with immunotherapy versus immunotherapy and a targeted medication.
Tian Zhang, M.D., M.H.S.: In kidney cancer, we talk about localized regional disease with lymph node involvement or distant metastases spread to distant organs. For these patients, often the localized disease settings are treated with surgery. In those cases, the five-year relative survival rates per the SEER databases are quite high, about 93% in regional disease, so patients who have lymph node involvement. For example, these patients often have a five-year survival rate of around 72%. And for patients with distant metastatic disease, the 5-year relative survival rate is around 15%. These are based on SEER population data from all the patients who are currently diagnosed and treated in the United States. As our treatment options improve for metastatic disease, hopefully, the long-term survival rates will also improve for patients with metastatic disease.
Risk for recurrence varies based on histology as well as patient risk factors. Often these depend on the size and invasion at the time of tumor removal. So when we’re talking about post-op patients and their recurrence risk, these often involve both their clinical and pathologic features at the time of surgery. There are good risk modeling calculators that we use to think about risk for recurrence, but these are really tailored for each patient.
Transcript is AI-generated and edited for clarity and readability.