"The time has come," the Walrus said, "To talk of many things: Of shoes--and ships--and sealing-wax-- Of cabbages--and kings-- And why the sea is boiling hot-- And whether pigs have wings." ---From The Walrus and the Carpenter, by Lewis Carroll (in Through the looking glass)1
“What’s going to happen to me now?” Colonel Das was looking at me expectantly.
Kolkata was my first placement as a gastroenterologist after passing DM in 1988. I was bubbling with facts and figures. “CT shows that your pancreatic tumor size is larger than 5 cm, and some lymph nodes are also enlarged. It is possibly stage 3. I will refer you to our oncologist who is an expert in cancer treatment.”
“And then?” He wanted to know more.
Without blinking I replied,”Well, it is one of the bad cancers and has gone beyond the curable stage. One year survival figures are reported to be around 20% in this stage.”2
I could see the shock in his eyes, “You mean 4 out of 5 people will die before 1 year?”
I nodded.”But we do have a very good onco-surgeon!” And I referred him to our oncology department, ending that consultation.
Soon after that I was posted out of Kolkata. About 10 years later, while I was at Army Hospital R&R, New Delhi, this gentleman walked into my OPD. He looked a little more grey, but fit otherwise. He placed his document-packet on my table and I immediately recognised my own handwriting in his old case notes. Our previous conversation came back to me.
Now Retired Brig Das, smiled at me as he saw the twinge of recognition in my eyes.
“I am not here for consultation this time. I couldn’t help it. When I realised that you are posted here, I thought I must see you. And tell you that I have beaten your odds!” His documents told me that he had had chemotherapy and surgery. His lymph node histology showed features of tuberculosis but no tumor, and he had been treated for it too. So he had been cured.
I smiled too, “Oh, Thank you. I am so happy for you.” Inside I was feeling embarrassed and guilty for giving him near hopeless prognosis, so many years back. What a devastating effect my words would have had on him then? He was magnanimous enough to forget that incident and we became friends.
But it had left me wondering whether my approach to prognostication needed to change.
There is another incident from the 1990s. One day our senior professor of medicine, and a well wisher, had called me aside in a meeting and told me, ‘AC, you have a deep ear lobe crease. It’s a sign that you are going to have a heart attack within next five years!’ I did not like his prophecy. Yes, I was overweight and exercised minimally. But I did not want to have a heart attack. He put me through a treadmill test and a multiple-gated acquisition (MUGA) scan. Fortunately these tests were normal. But every time I met him, he looked at me as if expecting a heart attack. It used to make me uneasy. It was much later that I realised that the ear lobe crease as a physical sign has very poor specificity. And the diagnostic value of treadmills in asymptomatic individuals was even worse! So far I have escaped my predicted fate, but I do not know which way the cookie will crumble tomorrow.
Every now and then, in Medicine, we extrapolate inferences drawn from the study of one population to individuals belonging to a different population. For example, all pre-marketing clinical trials of antihypertensive drugs are done on young adults while in real life the drugs are used often for elderly populations. It is only after years of experience that we learn that clinical trials results can not predict the responses in the real life situations. No wonder a large number of drugs have to be withdrawn years after marketing.3,4,5,6,7,8,9 In fact there is a famous quote by the dean (Sidney Burwell) of a famous medical school,”Half of what we are going to teach you is wrong, and half of it is right. Our problem is that we don’t know which half is which.“10 We are still not sure, what kind of research allows us to perform unnecessary surgeries11 even when evidence fails to confirm disease.12 I have now come to accept that ‘It is difficult to make predictions, especially about the future.’13 Let us see, ‘Why?”
While searching for information on prognostication in medicine, I came across an interesting paper in British Medical Journal that said,’When it comes to predictions, patients should not expect too much of our doctors!’14 The power of physics and mathematics to predict planetary orbits has given rise to the concept of determinism. The word ‘determinism’ is often used in philosophy to suggest that all events are completely determined by previously existing causes. It is the opposite of randomness.15 It works well if there is one cause and one direct effect. In very simple terms – if it rains, I will get wet. But the obvious caveat is that I should be standing under the open sky but should not be under an open umbrella.
Laplace is supposed to have said, “Given accurate positions and velocities for all the particles in the universe, and sufficient calculational power, it would be possible to determine the entire course of history.” What he said is a mathematical consequence of Newtonian mechanics.16
This statement has two major imperfections. First is that calculational power required does not increase in direct proportion to the number of particles and the time forward for which prediction is sought. In fact It increases exponentially. Secondly, it is not possible to find out the number of particles in the infinite universe. Thus, the flaws lie in the innocent words “accurate” and “sufficient” which fall in the realm of impossibility.
Predictions in medicine are much more complex than that, because (a) biological science is not a linear system with one cause leading to one effect17 and (b) there are so many undiscovered factors that can influence outcomes. Minute deviations in any or the preconditions can produce huge cascading effects. “For want of a nail the shoe was lost, for want of a shoe the horse was lost, for want of a horse the King was lost” encapsulates the matter rather well. Of course, the loss of the king could have so many other causes too! If predictions were easy, everyone would win at stock markets.
The word ‘Chaos’ has been used in the context of such complex ‘non-linear’ systems. Dictionary meaning of this word is ‘A state of total confusion with no order.’ From the scientific standpoint, it is the property of a complex system whose behaviour is so unpredictable as to appear totally random. Unpredictability is usually due to great sensitivity to small changes in pre-conditions.18
In other words, minuscule errors in measurements or rounding-off-decimals in numerical computation, can yield widely diverging outcomes for dynamical systems.19 It renders long-term prediction of their behaviour impossible as outcomes are dependent on multiple such series of events.20 Some have described it as the butterfly effect.41 Predicting earthquakes is an example of such a system.21
Human biology is equally, if not more, complex. Our knowledge is limited to a few gross facts. How genetic variables interact with organisms’ environment is not fully understood. How proteomics and metabolomics interplay in the microscopic cell is not fully understood. Theory of chaos is applicable to questions such as who will contract which disease? Or who will respond to which treatments? Or will this treatment work for an individual patient?
From the factors that are known, sometimes one may say with 95% confidence that ‘there are 60 (+/-20)% chances of event ‘x’ (For example death in 1 year).’ What will actually happen in an individual case remains unpredictable. Partly because our knowledge about factors affecting outcomes, and how these factors influence each other, is grossly incomplete.
In context of the recent COVID-19 pandemic, a systematic review on 41 papers on a drug (hydroxychloroquine) mentioned 10% of 1515 patients developed QT prolongation and 2 patients had arrhythmias.22 Can we predict, which patient will develop QT prolongation and which one will develop arrhythmias? Such predictions are currently classified under ‘predicting the unpredictable.’23
About 251,000 people in the United States die because of medical errors every year.24,25 If errors could be predicted, they would be avoided. Obviously all these patients must have been given a wrong prognosis in case they had asked!
We base our calculations or predictions on the basis of medical research. There are two unaccounted factors that can influence the results of medical research, and can make all conclusions and inferences erroneous. First is the zeal to publish ‘significant’ research. What all can be done to publish a paper has been analysed elsewhere.26 In addition, there is an element of bias in research.27,28 Many a times there is misleading interpretation of statistical significance tests.29,30
Second is deliberate introduction of bias or spin to give a different meaning to research.31 It is usually done for the personal gains by the author.32 Spin has been defined as a specific intentional or unintentional reporting that fails to faithfully reflect the nature and range of findings and that could affect the impression the results produce in readers.33 Several instances of fraud and falsifying have also been reported,34 but many more may have gone undetected.35
So, what do I do if, for example, my patient with fever asks, “how long will I take to recover?” I do take refuge in statistics, if it is known. ‘People take a median of 7 days to recover. Though some recover in a day while a rare one may take several months.’ I ignore the chances of deaths due to medical errors, and therefore I may not be accurate. On his or her part, my experience shows that most patients will usually register only ‘7 days’ and ignore the rest. Well, this is an innocuous example.
‘Doctor, am I going to die?’ seems a more serious and direct question. A doctor, depending on his experience may answer,”Everyone dies one day!” or “We will not let you die!” or “You have 30% chance of dying with this disease.” Some may confuse the patient by adding, ‘And I am 80% right 70% times!” But our experts in communication skills tell us that all these answers are wrong.
First we must understand what the patient already knows! Is he asking for reassurance? Or is he asking for information? Or he is just trying to confirm what his neighbour told him? Or is he trying to test the physician’s knowledge? An appropriate response can only be given after understanding these elements. So rushing to answer is not a good option.
Surprisingly the accuracy of predictions bothers the patients less than the ‘manner’ in which it is delivered. Main grouse the patients’ have is that the doctors are not compassionate enough.36 Patients seem to want several things from their doctor as per one study. That includes active listening, caring attitude and connection, respect, time, access, empathy, transparency, trust, clear instructions and effective communication.37 In India, the aphorism is that priority-1 for a patient is availability of the doctor, followed by doctor’s behaviour and least important is doctor’s competence.
Every doctor wants their patient’s to have full trust in them. It is clear that doctors have no clue how this trust can be earned.38,39,40 Using linear deterministic thought processes may be one of the problems. We hardly ever talk about our shortcomings in this regard. I think time has come that we did.
These days, when asked to give a bad prognosis, I find it simpler to confess to my patients that I am practicing an incomplete and evolving science. ‘I will try to answer your queries about the future on the basis of available data. The fact remains that nature has often proved me wrong.’
|↑2||Rawla P, Sunkara T, Gaduputi V. Epidemiology of Pancreatic Cancer: Global Trends, Etiology and Risk Factors. World J Oncol. 2019;10(1):10-27. doi:10.14740/wjon1166|
|↑3||Anand AC.Glasshouses and bioresonance therapy. National Medical Journal of India. 2012;25(6):365-8.|
|↑4||Kimberly A. Market withdrawal: Are our drugs really safe? Available at http://www.consumer-health.com/services/cons_take73.php|
|↑5||Eli Lilly Announces Worldwide Xigris Recall October 26, 2011. News item.Available at http://www.newsinferno.com/pharmaceuticals/eli-lilly-announcesworldwide-xigris-recall/|
|↑6||Silva E, de Figueiredo LF, Colombari F. Prowess-shock trial: A protocol overview and perspectives. Shock 2010;34 Suppl 1:48–53. Available at http://xa.yimg.com/kq/groups/16749867/1799940824/name/PROWESS-SHOCK%2BTRIAL.pdf|
|↑7||List of drug products that have been withdrawn or removed from market for reasons of safety or effectiveness. Available at www.fda.gov/ohrms/dockets/98fr/100898b.txt|
|↑8||Lexchin J. Drug withdrawals from the Canadian market for safety reasons, 1963–2004. CMAJ 2005;172:765–7.|
|↑9||Update on withdrawals of dangerous drugs in the US. Available at http://www.worstpills.org/includes/page.cfm?op_id=552.|
|↑11||Kwok AC, Semel ME, Lipsitz SR, Bader AM, Barnato AE, Gawande AA, et al. The intensity and variation of surgical care at the end of life: A retrospective cohort study. Lancet 2011;378:1408–13.|
|↑12||Flum DR, Morris A, Koepsell T, Dellinger EP. Has misdiagnosis of appendicitis decreased over time? A population-based analysis. JAMA 2001;286:1748–53.|
|↑14, ↑16||Firth WJ. Chaos–predicting the unpredictable. BMJ. 1991;303(6817):1565-1568. doi:10.1136/bmj.303.6817.1565|
|↑17, ↑19||Higgins JP. Nonlinear systems in medicine. Yale J Biol Med. 2002;75(5-6):247-260.|
|↑20||Kellert, Stephen H. (1993). In the Wake of Chaos: Unpredictable Order in Dynamical Systems. University of Chicago Press. p. 32. ISBN 978-0-226-42976-2.|
|↑22||Jankelson L, Karam G, Becker ML, Chinitz LA, Tsai MC. QT prolongation, torsades de pointes, and sudden death with short courses of chloroquine or hydroxychloroquine as used in COVID-19: A systematic review [published online ahead of print, 2020 May 11]. Heart Rhythm. 2020;S1547-5271(20)30431-8. doi:10.1016/j.hrthm.2020.05.008|
|↑23||Schwartz, P. J., & Woosley, R. L. (2016). Predicting the Unpredictable. Journal of the American College of Cardiology, 67(13), 1639–1650. doi:10.1016/j.jacc.2015.12.063|
|↑24||Anderson JG, Abrahamson K. Your Health Care May Kill You: Medical Errors. Stud Health Technol Inform. 2017;234:13-17.|
|↑25||Makary Martin A, Daniel Michael. Medical error—the third leading cause of death in the US BMJ 2016; 353 :i2139|
|↑26||Anand,A C. ‘Research in India’, Speaking for myself, Natl Med J India. 2017 Jan-Feb ;30(1):39-42.|
|↑27||Gerhard T. Bias: considerations for research practice. Am J Health Syst Pharm. 2008 Nov 15; 65(22):2159-68.|
|↑28||Pannucci CJ, Wilkins EG. Identifying and avoiding bias in research. Plast Reconstr Surg. 2010;126(2):619-625. doi:10.1097/PRS.0b013e3181de24bc|
|↑29||Pitak-Arnnop P, Dhanuthai K, Hemprich A, Pausch NC. Misleading p-value:do you recognise it?. Eur J Dent. 2010;4(3):356-358.|
|↑31||Every‐Palmer, S. and Howick, J. (2014), EBM fails due to biased trials and selective publication. J Eval Clin Pract, 20: 908-914. doi:10.1111/jep.12147|
|↑33||Boutron I, Ravaud P. Spin in biomedical literature. Proceedings of the National Academy of Sciences Mar 2018, 115 (11) 2613-2619; DOI: 10.1073/pnas.1710755115|
|↑34||Pollock AV, Evans M. Bias and fraud in medical research: a review. J R Soc Med. 1985;78(11):937-940. doi:10.1177/014107688507801113|
|↑38||Pearson SD, Raeke LH. Patients’ trust in physicians: many theories, few measures, and little data. J Gen Intern Med. 2000;15(7):509-513. doi:10.1046/j.1525-1497.2000.11002.x|
|↑40||Anand AC. Indian healthcare at crossroads (Part 1): Deteriorating doctor-patient relationship. Natl Med J India. 2019;32(1):41-45. doi:10.4103/0970-258X.272117|
|↑41||Lorenz, Edward N. (March 1963). “Deterministic Nonperiodic Flow”. Journal of the Atmospheric Sciences. 20 (2): 130–141.Bibcode:1963JAtS…20..130L.doi:10.1175/1520-0469(1963)020<0130:dnf>2.0.co;2|