How Much Are We Over-Diagnosing Cancer?

The word about 'overdiagnosis' is a regular feature in medical journals, stories are found at least weekly in major newspapers, and patients are starting to question whether cancer screening tests are really right for them.

Victory!

Ok, no no, we are a long way from finding the right balance of too much and too little medicine. But now that we accept that 'too much medicine' is a real thing, we need to figure out just how big the problem is.

Peter Ubel (@peterubel) is a physician and behavioural scientist, and author of Critical Decisions (see this and related books on our list)

He has attempted to lay out the way in which we can quantify (and clarify) the times where we inappropriately give a person the label of 'cancer.'

He states clearly that misdiagnosis, while unfortunate, isn't overdiagnosis. He also says that false-positives, while they can lead to harmful results, are not overdiagnosis.

What is is then? Whole conferences (eg. Preventing Overdiagnosis) have been devoted to defining it. 

Overdiagnosis, according to Ubel, occurs when we detect things that would never have caused a problem for the patient. He gives the example of a tiny breast cancer that would never have been noticeable in an elderly woman (who would undoubtedly die of something else first). When trying to change the culture to encourage people to stay away from screening tests that will lead to overdiagnosis, we are up against several challenges. One of those is the fact that early diagnosis can sometimes make it seem like we live longer if we detect the cancer earlier, though finding it early doesn't improve or save our life (lead-time bias, which is explained in the article).

Ultimately, in order to quantify the prevalence of overdiagnosis, we will need population-level data after a screening program has been introduced, and the data will need to be measured for long enough that any of the lead time bias effect will have passed.

Read more of Dr Ubel's explanation, How Much Are We Over-Diagnosis Cancer? in Forbes.

Source: http://www.forbes.com/sites/peterubel/2015...

Why Survival Rate Is Not the Best Way to Judge Cancer Spending

The New York Times has a great piece on their Upshot blog about assessing value when it comes to testing and treating cancer. It can be very challenging to measure whether the money we spend on health care is providing good return, making a meaningful improvement for patients.

We want every dollar we spend to help people live longer and higher-quality lives. However, when data of survival rate is examined, it may lead to inaccurate conclusions about the effectiveness and worth of a test or treatment.

The Upshot expands upon Why Survival Rate Is Not the Best Way to Judge Cancer Spending. Dr Carroll explains how statistics - particularly the parameter of 'survival rates' - can mislead us into thinking we are helping patients, but because of lead-time bias and overdiagnosis bias, what we are measuring as "success" is not actually translating into improvement for the patient. Our mis-guided spending is leading to the point where we do not have money to spend on more impactful interventions. 

Read the article for clear explanations of these biases with illustrative examples, and consider that by focussing on the wrong measures, "we may be getting far less for our money then we think."

Source: http://www.nytimes.com/2015/04/14/upshot/w...