10-Year Cell Phone / Cancer Study Is Inconclusive

crimeandpunishment writes "A major international (retrospective) study into cell phones and cancer, which took 10 years and surveyed almost 13,000 people, is finally complete — and it's inconclusive. The lead researcher said, 'There are indications of a possible increase. We're not sure that it is correct. It could be due to bias, but the indications are sufficiently strong ... to be concerned.' The study, conducted by the World Health Organization and partially funded by the cellphone industry, looked at the possible link between cell phone use and two types of brain cancer. It will be published this week."

Comments

It's all relative

[phantomfive]

At least from this we know that cell phone radiation isn't causing some massive epidemic of brain cancer, and the affects, if there are any, are relatively small. That's not the biggest comfort you could have, but it's something (considering most of us are not going to give up our cell phones anyway).

Re:It's all relative

[WarJolt]

Most people who have high cell phone usage also share other behavior. CEO use cells a lot and have high stress. Stress is a key factor in a lot of cancers. It's hard to track the roots of the problem.

Re:It's all relative

[bjourne]

And some stress could certainly be caused by cellphone usage. Not that I'm disagreing with you. Creating fair studies that takes into effect all independent variables is hard.

Re:It's all relative

[jeff4747]

The fact they could find neither a conclusive link nor disprove one indicates they missed something which is likely associated.

They did disprove it. However, the study author and the reporter really, really, really wanted to prove it so it was reported as "inconclusive".

Re:It's all relative

[AK Marc]

Perhaps you could come up with an example where there is no correlation, but there is causation?

I always wonder when I get these "challenges" whether someone really doesn't understand how statistics work, so they are wandering around in a constant state of confusion (or worse, confident ignorance). Or whether they are all pedantic asses who are too lazy and/or stupid to have an independent thought.

I can think of trillions of examples of a causation without correlation. I'll stick to something related to this topic. People who use cell phones have different habits than those without. Perhaps, because people aren't tethered to the desk phone, when they take calls at a desk, they push away or are more likely to walk around. If the CRT radiation has a greater effect than the cell phone radiation, then you'll find a result that correlates cell phone usage with lowered cancer, even though cell phones cause cancer.

The short answer is "confounds." They are everywhere, and you eliminate as many as possible in a study, but you never know what you missed, and you find what you can, publish what you find, and if anyone else identified a confound that wasn't accounted for, they can re-run the study with that in mind to see if it had any effect.

But, that you can't think of even one possible solution to the question you asked means you are too narrow minded or too stupid to worry about. I'm just posting this for those that have reasoning skills left. It's like all the people here, especially when I see people talking about voting and balloting systems, where if they can't think of a solution to a problem, then it's somehow proof that the solution doesn't exist.

Re:Limited study

[Anonymous Coward]

Yeah, because surveying all those people would be ABSOLUTELY FREE and take NO TIME. Also, it's totally necessary to check everyone. Sampling and statistics don't exist.

How silly.

Re:Limited study

[goose-incarnated]

To get statistical significance, you don't need to sample the entire population. Beyond a certain number for a certain confidence level, you don't get very much more.

Re:Limited study

[The Snowman]

It seems silly to limit the study to 13,000 when the test pool is potentially in the millions.

Not really. Sampling can give accurate results even when sampling a small percentage of the total population. If U.S. political polls select a sample size of between a few hundred and a thousand out of 300 million with only 3% error, it sounds reasonable that 13,000 would be a good sample size of a population 20 times that, giving the same margin of error.

Also remember that, assuming the sample is chosen well (it is a good cross-section of the population and not confined to one specific subgroup), the benefits of adding additional samples drops off. It is essentially logarithmic: at first, adding samples is a huge benefit: after a certain point, the incremental gain from one additional sample is only a tiny fraction of the first samples.

Re:"Survey"?

[ph1ll]

And even if there is some correlation, people need to put it in perspective.

The last time I talked to a flat-earth-er about their fear of cell phones causing cancer, they had a drink in one hand and a cigarette in the other.

Now that, Alanis Morrissette, is irony.

Problem with surveys

[Chicken_Kickers]

I have a problem with "medical surveys" in that they a prone to make correlation-causation errors. This seems to be a measurable problem that can be tested in the lab. Why don't people do this instead. Put a lab monkey next to an active mobile phone and keep them there for several years. After that, dissect the monkey for any signs of cancer. If there is, then alert the public. You then look into how it happened, i.e the biochemical interactions that caused it. Just "surveying" people introduces biases, other factors like diet and lifestyle and also crackpots.

Re:Problem with surveys

[Anonymous Coward]

> I have a problem with "medical surveys" in that they a prone to make correlation-causation errors.
No they aren't. The people who conduct medical surveys such as this are invariably qualified epidemiologists who don't need to be told the difference between correlation and causation by some guy on slashdot.

Now, the media reporting of such surveys quite often conflates correlation and causation; see:

http://www.phdcomics.com/comics.php?f=1174

The final stage, not illustrated in the above diagram, involves some guy on slashdot conflating the actual surveys with media coverage of said surveys.

Re:Problem with surveys

[idealego]

It's not that simple. You're ignoring statistics. You'd need a certain number of monkeys and some of them would have to be controls. If the effect is predicted to be small you may need thousands of monkeys. Animal rights groups would have a fit over this.

The monkeys would also have to experience the cellphone radiation in a similar way that humans would. The radiation would have to be emitted as if a cellphone were pressed up against their ear, and it would have to be intermittent as to simulate a human taking calls throughout the day.

Different cellphone systems run on different frequencies. If there was strong evidence to suggest that one caused cancer we couldn't necessarily assume that they all do, including future networks running on different frequencies. The same could be said about the power of the transmitter--different phones transmit at different levels of power, and future phones may be very different.

Some researchers believe that some cancers may take much longer than 10 years to show, so a thorough experiment may need to last 30 years or more. By the time good data is collected the cellphone networks would probably be using different frequencies and possibly lower power transmitters.

I'm sure there are other factors that I'm not even thinking about. Setting up a bulletproof experiment of this nature and getting solid results in a reasonable period of time is at least difficult and maybe impossible.

Re:Limited study

[Threni]

No, you get a smoother, more natural bass and just generally a warmer...uh, sorry, wrong thread!

USA Today

[Nidi62]

The article in USA Today has a nice little gem in it: "The authors acknowledged possible inaccuracies in the survey from the fact that participants were asked to remember how much and on which ear they used their mobiles over the past decade. Results for some groups showed cellphone use actually appeared to lessen the risk of developing cancers, something the researchers described as "implausible."" Now, I don't know why, but something about this statement seems kind of important.

Re:Limited study

[SoVeryTired]

The principle is correct, but you're failing to take into account the probability of an the respective events. Given that winning 60% of the vote is considered a landslide, you can think of asking someone whether they're voting Republican or Democrat as a coin flip with a small bias in one way or the other. Because the race is so close, a few extra republicans or democrats in your sample won't produce a huge error in your estimate.

On the other hand, a brain tumor can be thought of as a rare event. If the true incidence rate of brain cancer is five occurrences per thousand people over ten years, and your sample of 1,000 people has six incidences, you have a sample error of 20%. It's because of this that a small variation in the numbers can produce a large error. Therefore if you want to accurately assess the rate of cancer, you need a much bigger sample size.

what?

[drDugan]

Science isn't inconclusive. There is statistically significant, or not. In this case, not.

Test another hypothesis or test again if data looks fishy.

Statistical significance

[icebike]

To get statistical significance, you don't need to sample the entire population. Beyond a certain number for a certain confidence level, you don't get very much more.

Exactly right.

There was no statistical significance, which means that the cancers (or absence there of) were distributed over cell phone users and non-users (controls) with no preference for either group.

Normally this would be the end of it.

But by the way the reporter worded it (Inconclusive) and (to a lesser extent) the way the Researcher phrased it, indicates a clear predilection toward finding a positive correlation, which they could not do.

The takeaway is not that the study "inconclusive". The scientific takeaway is that there is yet again no evidence of correlation between cancer and cell usage.

Its over. The absence of evidence destroys this theory. Time to move on.

Re:Statistical significance

[PopeRatzo]

Time to move on.

I'm not so sure. Cancer is a funny thing, and "cell-phone use" is kind of a broad behavior. I have seen so many items get shifted from the "causes cancer" to "inconclusive" to "completely safe" category and then back again, that I've got something of a jaundiced eye toward "moving on" based upon one study.

Even if you remove the obvious data-cooking by the industry, there actually were studies in the 50's that showed that the connection between cigarette smoking and cancer was "inconclusive". Better-designed studies, honest studies, showed later that the connection was real. We see this back and forth with dairy products and cancer in women, with certain chemicals in insecticide, with the ground water near industrial sites, with thalidomide. Sometimes it takes a whole bunch of studies before causal relationships are exposed. Sometimes, it takes a lawyer digging up studies done by the companies themselves and then supressed.

A few days ago, there was discussion here about h. pylori and ulcers. The first studies done by the Australian researchers came up inconclusive. Twenty years later, they got the Nobel Prize for later studies that proved the connection was there. Now, nobody has to suffer with ulcers any more, and ulcer surgeries are practically unknown.

No, you don't "move on" because of one study or maybe even ten studies. Science doesn't just drop an issue because of one researcher's findings. The reason this issue with the cell phones is even being looked at is because when you've got entire populations holding microwave transceivers next to their noodles day in and day out, you want to make sure it's really safe.