Am I Gonna Make It Doc?

Patients almost always want to know what will happen if they have some disease where their demise is imminent. The classic big guys remark about "Am I gonna make it doc?" often is the bravado covering abject terror.

In a recent NEJM article there is an interesting piece on prognostics in medicine. Namely we are all now seeing more and more survival curves, conjoined with prognostic tests which contain genetic information.

The patient wants to know but unfortunately the physician really does not have a clue. The article states:

We believe that at least as much attention should be paid to clinicians' communication about the uncertainty associated with prognostication as to the search for better prognostic models. We propose a framework of three central tasks that clinicians can perform to help patients and families manage uncertainty. Physicians should tailor this framework to the core values of the patient. Some patients will value quality of life more than quantity of life, and for these patients uncertainty about future well-being may be of greater concern than life expectancy.

 My concern about better prognostics fall in the following categories:

1. Prognostic data on survival work only for large groups not for a single patient. When I look at the Kaplan Meir survival data for such therapeutics as those new ones for melanoma and even for transplants for MDS I see a 20-30% survival at the tails. To me that tells me something, besides the patient who hope to be the tail. I ask why that group, what happened there? Unfortunately we all too often do not have an answer.

2. Prognostic data is now being used by the Government, namely CMS and under the ACA, for treatment directives and physician control and compensation. Just look at the prostate cancer debacle. The "Committees" making the decisions have decided that PSA tests are useless so they will soon disallow them. They may be useless for some but not all. Yet to the "Committee" they apply to all, a classic Soviet style prognostic decision process.

3. Genetic Tests Yield Prognostic Data: With the ability to collect massive genetic data from genes to SNPs we now have researchers announcing new prognostic tests which at best are problematic and at worst harm the patients. The problem is that all too often one can statistically get "prognostic" data from any correlation, meaningless as it may be.

4. Prognostic Data on Survival Applies to Only Some: I read a recent paper on MDS survival and was truly disappointed by what was in my opinion poor statistical analyses. It compared low risk and high risk patients undergoing bone marrow transplants. It showed the higher risks with better survival. It also showed the higher risk having initially a faster drop in Kaplan Meir at the beginning and then a sustained flattening at 30%. Why? One reason may be that the one who died early had poor HLA matches while those who survived had better, say 10 point match to a 5 point match. But such an analysis was not to be,

The article then states:

Prognosis, and prognostic uncertainty, have a profound influence on physicians, as well as on patients and families. Physicians' generally optimistic bias is well documented. In one study, physicians overestimated the likely duration of survival of terminally ill patients by a factor of five, and the longer the duration of the patient–physician relationship, the more optimistic the estimate. Clinicians may also have trouble with prognostic uncertainty. Some react with an unwillingness to talk to the patient about the future at all (but commonly express this unwillingness in terms such as “we have to wait and see” or “no one can tell”). Others, ignoring the uncertainty inherent in prognostication, do more and more tests in the futile hope of improving their prediction. We believe that physicians need to recognize their reaction to uncertainty and how these reactions may influence their conversations with patients.

 The question of what is going to happen is always on the mind of a patient and their family when a severe diagnosis is made. All too often the physician just does not know. The lung cancer patient who on average is supposed to be dead in three months but lasts three years. The pancreatic cancer patient who also was to last three months but dies of old age. They may be the exceptions but our prognostic capabilities are still quite weak, except on the average. Yet we have never seen an "average" patient.