Mammograms, PSA Tests, and PAP Smears: The difficulty in screening for cancer

Within a few years, cancer is on track to overtake heart disease as the #1 cause of death among Americans, and one out of every two of us is expected to be diagnosed with cancer at some point in our lives.  Cancer is extremely prevalent, and a big question is how best to fight it.  History has shown us that the survival rates are much higher when treating cancer in its earliest stages, and so one main focus of our healthcare system is to diagnose cancer as soon as possible.

I think almost everyone has had at least some experience with cancer screening.  We are always told to check ourselves for suspicious lumps or weird pains - things like breast or testicular self-exams.  We also undergo screening during our annual checkups.  Mammograms (breast cancer), prostate-specific antigen tests (PSA, prostate cancer), colonoscopy (colon cancer) and PAP smears (cervical cancer) are the most common.  Other tests that can be used are chest x-rays (lung cancer) and MRI or CT scans (for anything else).

Yet if you read the news, there seems to be a lot of controversy over what kind of tests are necessary.  Recently, the US Preventative Services Task Force advised that healthy men should not receive PSA testing.    The same task force has also advised against mammography for women under the age of 50.  At first glance, this may seem odd - if there is a test that can diagnose cancer, why not perform it all the time?  

A good test must be able to accurately detect when cancer is present.  But what many people don't consider is this: what happens when the test is wrong?  In this post, I'll go over some of the science of screening for cancer, and hopefully explain why the guidelines are set the way they are.

Read more after the break.

False Positive

If a screening test was perfect, there would only be two possible results - a patient has the disease and the test is positive, or they don't have the disease and the test is negative.  In reality, tests can yield the wrong result.  Perhaps the patient has the disease but the test is negative - this is called a "false negative."  This can give false assurance to the patient or doctor that cancer isn't present, or delay possibly-needed treatment.  Luckily, the rate of false negatives in cancer screening is low.

The other type of error is a "false positive" - the test wrongly asserts that the patient has a disease.  This error may seem harmless, right?  Further testing would clear up any misconceptions.  But in reality, a false positive diagnosis can cost the patient a lot of stress, time, money, and in the worst case, damage their health.  And if the underlying rate of disease is low, the false positives can outnumber the true positives.

Consider a hypothetical screening test for cancer.  Let's say 1% of patients have the disease, and the screening test has a 5% false positive rate.  The number of false positives will outweigh the true positives 5 to 1.

CANCER SCREENING: A hypothetical screening test for some type of cancer that afflicts roughly 1 in 100 people.  The test has a 5% chance of returning a false positive result.  If 100 people are screened, we expect 1 person to actually have the disease (and test positive) and 5 people to falsely test positive (even though they do not have the disease).

So why is this bad?  Let's consider the case of the PSA test.  Blood is drawn and examined for molecular signs of prostate cancer, and is generally administered to older men during their annual checkup. PSA is a specific molecule that is generated by prostate cells, and if there is a population of overactive cells (like cancer) then this molecule can be detected in the blood.  However, there is always a baseline level of PSA circulating in any male.  By checking PSA levels annually, a doctor can identify an abnormal rise in PSA concentration, which could signal that cancer has arisen in the prostate.  PSA testing is cheap and easy, since all it takes is a simple blood draw and antigen test to look for signs of cancer.

The problem is that many other things could cause PSA levels to rise, and in and of itself, a high value is not indicative of cancer.  If the PSA test is positive, the next step is usually to perform a biopsy of the prostate and look at the cells under a microscope.  This will ultimately establish whether or not the patient has cancer.

To get a sample of prostate cells, a needle must go from outside the body to inside the prostate - there's no way around it.  There are three ways to do this - transrectally (most common), through the urethra, or through the perineum.  Not only is this extremely uncomfortable/painful, it can be dangerous. For instance, a transrectal biopsy goes from the rectum (a reservoir of bacteria) into the prostate.  In rare cases, prostate biopsies can lead to life-threatening infections.

The Upside

A good screening test will have minimal downsides, but a truly effective one must also demonstrate measurable benefit to the patient.  As it turns out, this is difficult in practice. What metric is useful to show the effectiveness of a screen?

One intuitive metric (commonly used in other fields) is survival - how long does the patient live from the time of treatment?  This is a great way to compare, for instance, two drugs.  If patients survive for 5 years on Drug A, but 10 years on Drug B, then it is clear which one is doing a better job to treat the disease.  But in screening, things are a little more complicated, and early detection through screening can distort the way we measure survival.

Let's suppose a person has unfortunately developed a very aggressive form of cancer, which has very limited treatment options.  In the figure below, I've plotted two possible courses for their disease.  In the top half, the cancer is detected by screening, and treatment begins.  But due to the lack of an effective treatment, the cancer continues to grow and the patient dies.  On the bottom half, the person does not undergo screening.  Their cancer is detected when they develop serious symptoms from the growth of the disease, and they also undergo an ineffective treatment.

Note that, with early detection, the patient was treated sooner, but that the time of death was still the same.  Since there wasn't an effective treatment, it didn't matter that we found the cancer early.  If we measure the effectiveness of our screen by recording the time the person lived after their treatment, we may come to the erroneous conclusion that we had some effect.  This is called "Lead-Time Bias."

For this reason, survival is NOT the way to evaluate a screen.  This effect actually lead people to believe that chest x-rays were an effective screen for lung cancer in the mid-1900's.  Now we know otherwise.

The best way to measure the effect of a screen is to look at the percentage of people dying of that disease (otherwise known as the mortality rate). If a screen is worthwhile, it will reduce the chances of dying from that type of cancer.  This is what we think intuitively when we consider whether or not to undergo a test.

But testing for mortality rate is very cumbersome, especially in screening.  Consider mammograms.  Most women begin to undergo regular mammograms in their 40's, and it may be many years for a particular woman before a test comes back positive.  If cancer is present, then treatment will be administered; in the unfortunate event that the treatment is unsuccessful, then it may be many years on top of that before the woman succumbs to the disease.  If one wishes to study the relative effectiveness of mammograms, then clinical trials with hundreds of thousands of women are needed.

A Tradeoff

All the negative emotional and physical side-effects of screening errors are called "morbidities," and for a screen to be effective, the benefits gained through correct diagnoses must outweigh them.  In other words, the test must have a higher chance of improving your life (by catching a potential life-threatening disease in an early, treatable stage) than harming it.  

Differences in this tradeoff are what drives the controversy over screening.  This is because the risk of cancer is different for people with different ages or family histories.  In the first figure, the true positive rate is 1%.  However, if a person had a 20% chance of having the disease, then the true positives would outweigh the false positives 4 to 1. This would likely make screening worthwhile.  However, if the true positive rate is 0.001%, then we would never screen using a test with a 5% error rate.  In addition, our data on the effectiveness of screening is constantly being updated.  It takes many years of followup to truly establish the effectiveness of the screen.  This is why the recommendations keep changing.

All this approaches the problem from a public health perspective, but it ignores the effects on an individual level.  For some people, fear or worry about cancer may be extremely detrimental to their quality of life.  In these cases screening can provide some mental relief.  So don't let what I've said deter you from undergoing screening if you worry about cancer.  But keep in mind that the people analyzing these screens pour over the epidemiological data, and don't make these kinds of recommendations lightly.  The full list of recommendations for cancer screening in adults can be found here.