Medicine is broken.
"We are going to see that the whole edifice of medicine is broken, because the evidence we use to make decisions is hopelessly and systematically distorted. And this is no small thing. Because in medicine doctors and patients use abstract data to make decisions in the very real world of flesh and blood. If those decisions are misguided they can result in death and suffering and pain."
The whole book is written to defend the following paragraph:
Drugs are tested by the people who manufacture them, in poorly designed trials, on hopelessly small numbers of weird, unrepresentative patients, and analysed using techniques which are flawed by design, in such a way that they exaggerate the benefits of treatments. Unsurprisingly, these trials tend to produce results that favour the manufacturer. When trials throw up results that companies don’t like, they are perfectly entitled to hide them from doctors and patients, so we only ever see a distorted picture of any drug’s true effects.
Regulators see most of the trial data, but only from early on in its life, and even then they don’t give this data to doctors or patients, or even to other parts of government. This distorted evidence is then communicated and applied in a distorted fashion.
In their forty years of practice after leaving medical school, doctors hear about what works through ad hoc oral traditions, from sales reps, colleagues or journals. But those colleagues can be in the pay of drug companies – often undisclosed – and the journals are too. And so are the patient groups.
And finally, academic papers, which everyone thinks of as objective, are often covertly planned and written by people who work directly for the companies, without disclosure. Sometimes whole academic journals are even owned outright by one drug company.
Aside from all this, for several of the most important and enduring problems in medicine, we have no idea what the best treatment is, because it’s not in anyone’s financial interest to conduct any trials at all. These are ongoing problems, and although people have claimed to fix many of them, for the most part, they have failed; so all these problems persist, but worse than ever, because now people can pretend that everything is fine after all.
"It's possible for good people in perversely designed systems to casually perpetrate acts of great harm on strangers - sometimes without ever realizing it."
The book is for everyone. This is pop science, so it will not contain fine details.
Systematic reviews highest quality.
Chapter 1: Missing Data.
Company funded studies produce more positive results than independent (or government funded) ones. 22% more likely to be positive. For their own drugs 78%.
Systematic reviews show companies give positive results 4 times more likely for their drugs.
Hiding negative results.
Tricks to make all company sponsored studies positive.
Why missing data is important. Rebocsatine for depression. Even when you're doing your best as a doctor reading the data and critically appraising it, you can still be mislead, because much data -often negative/bad results- is not published.
This is still happening, all over the world, for all drugs, and it's entirely legal!
TGN1214 trial on humans. Disastrous side effects. Not published data could have prevented it.
80% of first on human studies are not published even after 8 years.
This is about real people who die due to not publishing (e.g anti arrhythmatic for MI patients killed ~100k people, while publishing a study could have prevented this).
Importance of systematic reviews. Steroids for premature births. Meta-analysis. Blobbogram (aka Forest plot). Cochrane reviews.i
Study on anti-depressants in 2008 about drugs from 1987 to 2004 showed there were 38 positive results and 37 negative. In the Academic journals these translated to 48 positive and 3 negative results! Such distortion..
The evidence is overwhelming that negative trials are published less often or changed to appear positive. This is a systematic problem for all drug companies. This can cause unnecessary harm, suffering and death. Also it fools governments into oaying more money for expensive drugs that may be just as good as the old cheap ones.
Even in other branches of science, nefative results are less likely to published than positive results.
Journals are not to blame.
Not publishing negative results is unethical. Universities ans wthical committees have failed us.
Companies have the right to stop some studies at anytime for any reason. This introduces huye amount of bias and is not mentioned in the literature. They also can choose not to publish studies. And who can see the data; they can even prevent researchers working in the trial from analyzing and sharing data.
Researchers who try to fight the system are intimidated.
Patients are lied to by consent forms since if data is not published this does not lead to increase in our knowledge. Recruitment is already hard, this only makes it worse.
Suggests many solutions for the problem including setting trial registers.
Pre-registration as a condition for publishing in well known journals. Didn't work. Wasn't applied on ground.
EU register kept secret. Why call it a register if it's not public?
Lists many solutions by EMA EU and FDA that didn't work. Fake assurances.
Problems faced when trying to get data from regulators:
1. Information is held from regulators. Done legally. Prescription for other uses with no separate market approval as formally required (i.e. off label). Patent extention. (GSK paroxatine for children. Ineffective and leads to increase in suicide. Prescribed off label).
2. Regulators make it hard to access the data they do have. Messy websites. Documents with no title or table or contents.
3. Regulators withhold study records that they do have. Protection of commercial interests of companies, or personal data. Really? The EMA (EU regulator) was complicit with the companies and withheld data under fake excuses.
Regulators don't understand the difference in decision making they have to do (wether the drug should be in the market at all) and that done by doctors (is this drug suitable for this specific patient in front of me). They paternalisticly think they made the checking for doctors who don't need to get all the data.
Summary at end of chapter. This us research misconduct on a grand universal scale.
Tamflue case. Chochrine makes a mistake in their systematic review. Because their methods are transparent, this mistake is picked up by a Japanese doctor. They started working to fix this. Rosh, the company manufacturing tamflue held back the needed data. Discrepancies in data given to different regulators. The trials were designed to give favorable results.
Regulators are fallible. Rosey Glitazone for DM causing increased risk of heart problems.
Benifits of data sharing and how it leads to great results. Suggestions to increase public sharing of data.
Chapter 2: Where do new drugs come from
3 phases then regulator.
Ethical problems for trial participants. People who earn living from participating in trials (Genie Pigs). Abuses they endure and intimidations.
Commercialization of trials (CROs). Moving trials to low cost countries: e.g. India, China, Romania and Argentina.
This raises ethical (abuse, fairness) and scientific questions (quality, applicability etc). The Helsinki Declaration is not respected and recent changes made it ok to violate it while outside US and EU.
Chapter 3: Bad Regulators, getting your drug approved.
Pressures on regulators. Sociology of regulators. Regulatory Capture. Free movement of staff. Conflicts of Interest (in FDA etc who have commercial conflicts of interest). Corruption evidence very hard to gather in these situations.
The FDA has become an agent of the industry!?
Drugs in trials on patients should be compared to the current best treatment of the condition, and not to placebos. The Helsinki Declaration was amended in 2000 to specifically emphasize this point.
The parameters taken into account are sometimes not mortality and MI rate, but blood cholesterol levels (LDH etc). This can be misleading as surrogate outcomes don't always lead to the results we want. Example of CAST trial on anti-arrhythmatics for MI patients such an example. The rhythm was fixed, but mortality rate increased!
Accelerated approvals. FDA performance was assessed for decades by number of drugs approved per year which led to the "December Effect" with many drugs rushed in last weeks of year. Companies of course push for fast approvals for more profits. Urgent approval policy created after HIV epidemic. Abused by companies for drugs such Milidrum. Patient advocacy groups pressure. Post-approval trial promises are usually not fulfilled. Case of Iressa for small cell cancer.
Effects on innovation. If companies don't have to produce drugs better than those already available, they simply won't. This keads ti the "me too" phenomenon where instead of developing new drugs companies just manufacture their own drug of the same class e.g. SSRIs. Leads to waste of money time etc instead of developing new good drugs.
"Me again" phenomenon, changing enantima from right handedness to left handedness e.g. omeprazole and S omeprazole (Nexium).
Comparative effectiveness research. Vital.
Government should fund research. The price of overpriced medications outweights the price of doing research (to prevent it). e.g. treatment of hypertension amlodipine vs chlortalidone (cheap as effective and with no serious side effects).
Monitoring side effects. Spontaneous reporting. Database studies.
Regulators have a big duty to report side effects. A separate organization should be set with powers to withdraw drugs from market. Suggests solutions.
Chapter 4: Bad Trials
Tricks:
1. Outright fraud.
2. Test your drugs on ideal patients.
3. Test your drug against something useless (wrong dose, rotue, freq etc).
4. Make trials too short (surrogate measures).
5. Stop trials early (peeking, major side effects).
6. Stop trials late.
7. Small trials
8. Packaging/mixing findings
9. Per protocol vs intention to treat analysis.
10. Switching the primary outcome after the study ends. Drawing the target after you throw the dart.
11. Dodgy subgroup analysis (patients). Cherry picking among false positives.
12. Selective use of trials.
13. Seeding trials. To advertise drugs to doctors under the guise of research.
14. Pretend it's all positive regardless. Relative risk and absolute risk. Numbers needed to treat.
15. Industry funded systematic reviews!
Chapter 5: Bigger Simpler trials.
Observational studies. Take data from doctor notes without needing to make big costly trials. Statins (simvastatin and atolvastatin). What if this becomes the normal state of affairs, trial as a routine continuous activity in all clinical practice.
Ethical committees being an ass sometimes and putting unnecessary barriers for useful studies (20 mins consent form).
Chapter 6: Marketing
Doctors can read all papers. We need ways of communicating new information to doctors to save costs and increase efficiency.
Companies teach doctors aftet they graduate. Hold conferences. Many covert ways of advertisement. They spend twice on marketing and promotion than on R&D. Marketing is used to pervert the evidence-based practice.
Ads to patients directly. Only few countries allow this. Changes patient behavior to the worse. People are turned into patients. News drugs get more ads. It is people and patients who pay for the ad campaigns as the cost of drugs goes up due to ads.
Celebrity endorsement. Use of individual stories to market it. Depression-serotonin relationship has little support in academia. Pathologizing of normal human experiences, disease mongering. SSRIs and depression checklist.
Social anxiety disorder. Female sexual disfunction.
Patient groups. Drug reps. Free meals. Dealing with doctors based on their type. Gifts. Tricks. Flights. Entertainment. IMS data show to drug companies what doctors prescribe and so they double check on their promises. There are other ways to get the data too.
Don't see deugs reps and ban them from your faculty. Drug rep ban stand. Other advices.
Ghost writers of journal academic articles.
Academic journals. Their income from advertisement is mainly from pharmaceutical companies. Reprint orders. Conferences as trade fairs. CME teaching most sponsored by big pharma and used to promote drugs including those to be used off label and other tricks/transgressions.
We need proper regulations on Big Pharma and not an outright ban. Conflic of Interest should be declared. Other conflicts of interest not related to Big Pharma.
Afterward: Better Data
Missing data is biggest problem. All distortions can be corrected by check systematic reviews, but missing data cannot; it poisons the well for everyone, rich and poor.
Defends the book against predictable replies & criticisms and moves to the attack!
Many parts contain Bombardment of information, even for me. Too much details. It's on the borderline between pop science and science.
At end of each chapter suggestions to what to do. Book is partly written to doctors and partly to normal people/patients.