Clinical-Trials Books

I've bought this book last fall 2008 and i've read it to have an idea about clinical trials. The author was really crystal clear in explaining the theory behind clinical trials, the procedures involved, and the role of the statisticians in the trial. Anyone interested in this book should have background in Mathematical Statistics and SAS since the exercises involved math and SAS. If you are really interested in becoming a statistician for companies working on drug research, medical products and process development, then this book is a good text/reference for you to read and study. Overall, i think this book is very informative since the author had years of first hand experience as clinical trial statistician and professor of Statistics in the university.

I should begin by admitting that I had the opportunity to review this little masterpiece in manuscript. Good then, it's even better now.

It's good because it informs the reader, in sober prose, how to determine what works and what doesn't in medical practice, and what's safe and what isn't. It's good because it reveals what can go wrong when anecdotes ("it worked for me!") substitute for sound research as the basis for clinical practice. And it's good because it shows how serious are the consequences of even subtle failures to observe protocols in designing and carrying out clinical trials.

It is reassuring to read of the care and precautions advocated for government-sponsored research; it is accordingly unsettling to contemplate the pressure that commercial interests (drug companies, for-profit hospitals, equipment manufacturers) might bring on researchers to cut a few corners.

After reading "Clinical Trials" I came to appreciate that case studies, longitudinal studies, and retrospective questionnaires, so frequently hyped in the press and on television, are no substitute for actual well-designed and well-executed experiments. Because you and I are different, certainly genetically and probably in other essential ways, what helps you may well harm me. Only the proper application of statistics in designing clinical trials and in analyzing data from them can distinguish what's generally valuable from what's useless (however plausible and authoritatively touted it may be). Although the authors had the good taste to reject the aphorism, usually attributed to a nameless statistician, that "if experimentation be the queen of science, then statistics stands as the guardian of the royal virtue", its pithiness may give the reader the crucial insight into why alternative modes of research are untrustworthy.

Some readers may feel disheartened to learn the truth that many, probably most, promising therapies prove, when adequately tested, worthless, and some may feel in some fuzzy way that to accept this reality is cruelly to deny hope to those who need it badly. On the contrary, this book makes it clear that to offer false hope is the ultimate cruelty, for without experimentation there can be no knowledge, and without knowledge there can be no real hope.

Notwithstanding the slightly technical nature of this book (yes, there IS a chapter with mathematics), I recommend it highly for the general reader who is interested in such topics as personal health care, alternative medicine, managed care cost containment, and the like. Buy a copy for yourself, and, if you feel philanthropic, you might consider donating a copy to your health care provider. The world would be better if doctors' waiting rooms (like hotel rooms with their Gideon Bibles) all had a copy of "Clinical Trials in Oncology" available for patients' perusal.

I found this book almost 15 years ago when first designing a series of clinical trials for cytomegaovirus prevention in organ transplantation. It is a very practical "how to" volume, extremely well written and concise. I recommend this to all clinical investigators who are starting out, and for all trainees. I have been waiting for his revised edition for over a decade and only hope he will update this great book.

As his author himself has stated, this book is now out ofprint. As a researcher, I think this book is very useful, particularly to those who are just beginning their path in clinical trials; the book contains abundant information, as well as practical examples that make it easy to comprehend the basis of this kind of study; I think the chapter on sample size ism an especially interesting reading. In my opinion, this book deserves (and needs) a second edition, one in which some of the innovations could be included and some gaps could be filled; maybe a chapter about meta-analyses might be added.

Good evening, Iam a neurologist in the Mexican Institute of Social security, I'm study about de epidemiological clinic diplomate. I'm searching the relationship betwen sleep disorders and epilepsy and cephalea. My intention or purpose is for my doctoral studies, to make a protocolum in this topic. Thanks for all atentions Vic Martin Peres Sur 39-429 Orizaba,Ver. México.

Stephen Senn is a great writer and an excellent applied statistician. He has written a number of excellent books related to the conduct of clinical trials. This is the second edition of the book and it is even an improvement of the first which was also excellent and often consulted! A nice thing about Senn with all of his books is that he does not shy away from controversy. He also is very careful in his presentation and he avoids common mistakes and points out the mistakes of others.

I recently got a deeper appreciation for this book when I had to design a crossover equivalence trial while I was employed at Auxilium about 10 months ago. Senn does a very thorough job of explaining the AB/BA design which although simpler than many of the others is commonly used. Most of the important concepts in cross-over designs such as the washout period and the within subject variability can be address in this simplest of cross-over designs. This book is an excellent reference for any statistician that gets involved in cross-over trials. It is clear concise and strong on concepts but also detailed enough to make the correct mathematics clear.

Cross-over trials have the advantage of potentially reducing variability since each subject acts as his own control. But to avoid confounding, a washout period with the subject off treatment is required so that the effect of the earlier treatment is not influencing the results for the next treatment. Sometimes this constraint can make recruiting difficult and there can be other logistic issues that can make it infeasible.

DATA MONITORING IN CLINICAL TRIALS, by DeMets, Furberg, and Friedman, is 374 pages long. There are three chapters totaling 49 pages, followed by 29 case histories, each about ten pages in length. The first three chapters provide narratives to the case histories. Thus, the reader knows when to jump ahead in the book to one or more of the case histories, depending on his or her interest. Although the book is "about" Data Monitoring Committees (DMCs), the book provides guidance to most aspects of managing a clinical trial. This book discloses many subtle facts on the logistics of clinical trials, including how various groups (DMC, Institutional Review Board, study subjects, sponsor) are supposed to communicate with each other. In view of the excellent guidance provided by this book, I would recommend DATA MONITORING IN CLINICAL TRIALS to all managers and medical writers involved in clinical trials. The book walks the reader through many interesting decision-making trees.

My criticisms are that the book fails to provide any examples of a DMC Charter or a DSMB Charter, fails to provide an example of a DMC's recommendation or report, and that chapter 3 is on the sketchy side.

In chapter 1, we learn that the main purposes of a DMC is to ensure that subjects are not being harmed by the study drug or by the standard of care, and to ensure that the Clinical Study Protocol (CSP) is being followed (page 3). We learn that, for small single-center studies, an Institutional Review Board (IRB) is sufficient to do this job, but that for multi-center studies, both an IRB and DMC are needed. We learn that DMC had its origin in the "Greenberg Report" from 1967. The Greenberg Report was innovative in that it provided for an independent board (independent of investigators) that received study data, and where this data was kept secret from the investigators.

MEMBERSHIP OF DMC. Regarding members of the DMC, we learn that "the more distant and independent the better, but complete independence from the sponsor should not come at the expense of needed expertise" (page 6). We learn that DMC members must disclose conflicts of interest, on an ongoing basis during the clinical trial. We learn that DMC meetings have an open session component, dealing with administrative issues, baseline data, and adherence to the CSP, and a closed session, where unblended data is discussed. Administrative aspects include, e.g., are the subjects completing their forms; are subjects being enrolled on a timely basis; are the subjects adhering to the drug regimen?

We learn the definition of clinical equipoise: The state of not knowing which of the study arms is preferred, and gives the best results, as far as efficacy and safety are concerned.

We learn these things. The DMC needs to be alert of other trials using the same drug (pages 10 & 32, Cases 2, 8,15, 24, 27). Regarding other trials, the authors caution that study design may differ, for example, the relative time between the myocardial infarction and time of first administering the drug (the 2 studies were judged not likely relevant to each other) (page 32). The DMC may, if needed, recommend modification or termination of the present clinical study depending efficacy and safety results from the other trial (page 10, case 24).

RECOMMENDATIONS FROM A DMC. We learn that the DMC can recommend extending a trial, where the rate of outcome (primary variables) is too low, and that this strategy can be built into the CSP (page 11, Cases 8 & 27). We learn that the DMC can recommend stopping for (1) Overwhelming evidence for efficacy, (2) Serious harm, (3) Hopelessness that the study drug will work (Case 3), and (4) Extremely poor compliance by subjects with the CSP, and (5) Evidence from another trial that the drug works (or fails to work) (page 10). We that if changes are to be made to the CSP, they should be made sooner, not later (page 16, Case 27). We learn that where changes are made in the CSP, the FDA can become suspicious that the sponsor had a knowledge of the results (efficacy data and safety data) (page 43). In other words, the problem is that the sponsor can change the nature of the primary endpoint so that it is consonant with actual data that is coming out of the study population (pages 42-43). We learn of examples where the DMC was unable to provide a recommendation, and where an ad hoc committee or policy board was formed (pages 17, 29, 32 & Cases 12, 15, 18). We learn of the fact-pattern where the DMC recommended change in the CSP, where one change was a more stringent exclusion criterion, and the other related to drug administration (a slower drug infusion rate) (page 18 & Case 23). We learn this tidbit about scheduling DMC meetings--where materialization of certain adverse events (AEs) required the scheduling of an emergency teleconference by the DMC (page 19 & Case 16).

LAGGING DATA. We learn an interesting detail of the common problem of lagging reports from study subjects, where a "sweep" was implemented, where every subject was contacted at the same time (page 19 & Cases 9 & 22). We learn that under-reporting can result in an accumulation of data showing lack of efficacy (or poor safety) and that correcting the non-reported data can result in the disappearance of these disappointing trends (pages 20 & 24 & Case 22). We learn that the CSP should include a schedule for interim analyses (page 20 & Case 28). We learn of pre-determined stopping rules, where the rules were linked to the amount of data collected, and where stopping for benefit required data to be more convincing, than stopping for harm (page 21 & Case 19).

UNEXPECTED ADVERSE EVENTS. We learn that where an unexpected AE presents during a trial, e.g., cataracts or pulmonary embolism, this may require all study subjects to be informed of the risk, and to fill out a Re-Consent Form (pages 21 & 26 & Cases 7 & 17). We learn that a consent form is a contract between the investigator and subject (page 22). We learn of the hierarchy in obtaining data: data on mortality must be very current, data on serious adverse events (SAEs) must also be very current, data on primary outcome other than mortality can be a few months old, data on lab results and data on concurrent medications can also be old and not current (page 24). We learn that, at any given time, the DMC can choose to unblind the data or to maintain blinding (page 25 & Case 13). We learn that the sponsor can improve the efficiency of the DMC, by providing the DMC with a mock report at the DMC's first meeting (page 25).

EARLY DATA MISLEADING. We learn that early data from study subjects can be misleading, and that early trends can disappear later on (pages 25 & 31 & Cases 5, 11, 12, 17). Where the DMC can't decide whether to recommend stopping the trial or to recommend continuing, we learn that a third avenue is available--deciding to hold more frequent DMC meetings to evaluate incoming safety data (page 26). We learn the value of knowing the mechanism of a disease--where several symptoms are known to be part of the same disease, each of these symptoms can be listed as an outcome in the CSP, and a "composite outcome" can be set forth as an endpoint (page 26). A composite outcome is especially justified where each symptom responds in the same way to the study drug. For example, Case 10 discloses the composite outcome of death, infarction, and stroke (page 27 & Cases 7, 11, 27).

DEFINE SUBGROUPS. We learn of the advantages of defining subgroups (strata) in the CSP. For example, if an unacceptable AEs occur in the study, but where these are clustered in one of the subgroups, the DMC can recommend terminating this subgroup (rather than terminating the entire study (pages 28-29 & Case 12). We learn that the CSP must be written in a manner that adequately defines the subgroups. We also learn that what at first might be reasonable subgroups(ischemic and non-ischemic), turn out to be irrelevant to response of subjects to the drug (page 29). We learn that the group of subjects defined by a subgroup is not the same as a group of subjects presenting with a specific outcome for a surrogate marker, though these might seem to be the same, at first glance, to a layperson. We learn that it is preferable for a surrogate (or biomarker) to capture the full effect of the study drug (page 30). We learn of an example of surrogates (arrhythmia suppression; lipoprotein levels; cardiac function, microaneurisms) that were misleading, and that was not predictive of mortality or of coronary events (pages 30-31 & Cases 5, 13, 14, 17). We learn about follow-up procedures that occur long after the trial has ended or has been terminated early (pages 33-34, Cases 1, 12, 17). In Case 12, the trial itself showed no efficacy of the drug, while a follow-up after 9 years showed good effect. We also learn that studies can be terminated because the money ran out, or because the company changed hands (pages 34-36).

GOVERNMENT GUIDANCE ON ROLE OF DMC. Chapter 3 informs us on guidance on the nature of DMCs from the U.S.government ("Guidance for Clinical Trial Sponsors on the Establishment and Operation of Clinical Trial Data Monitoring Committees") and from International Conference on Harmonization.

INTERIM DATA. Chapter 3 provides interesting guidance on what to do with interim data. We learn about use of interim data (comprising data on surrogate endpoints such as viral load) and whether it should be used as a basis for stopping a trial for efficacy--we learn that it is more acceptable to stop a trial on the basis of interim data if the trial is nearly complete, and less acceptable to stop a trial still in its early stages (because that particular trial will not yet allow any valid conclusion) (page 42).

In chapter 3, we find a case history disclosing interactions between FDA, DMC, and sponsor, where the issue was agreement between interim data and data from a separate study on the same drug. The purpose of this commentary is to show how a DMCs decision can influence FDA's decision. The outside study showed that the drug worked. But the interim data showed that the drug did not work, and where the DMC recommended continuing the trial (until some difference might have materialized). After taking in all the information, including the info from the outside study showing that the drug worked, FDA required that the study be completed (page 47). Another case history disclose the situation where one sponsor was running several trials on the same drug, where each of these had its own DMC. In view of emerging safety issues from one of these trials, the FDA recommended that the manufacturer tell all of these DMCs to share safety data with each other (page 47).

Overall, chapter 3 is somewhat incomplete. This chapter would benefit by several more examples of interactions between DMCs and FDA. Apparently, the authors did not have much information to share on this particular topic.

RETINOPATHY CASE HISTORY. Case 1 concerns diabetic retinopathy, where treatment was photocoagulation (one eye treated, one eye not treated). Early results showed dramatic efficacy. The DMC recommended stopping the trial (and treating both eyes of each subject with photocoagulation), even though the trial was at an early stage, and only a few patients had been on therapy, and even though there was no opportunity yet to observe late complications. This posed a dilemma to the sponsor. The final decision was to continue the trial, but where both eyes were treated only in high risk subjects (high risk for blindness). This decision took the form of a compromise(pages 55-63).

PROPANOLOL CASE HISTORY. Case 2 (pages 64-72) concern the beta-blocker, propanolol, for treatment of myocardial infarction. Inclusion criterion was having a myocardial infarction 5-21 days before randomization. Case 2 provides useful nuts & bolts information for running any clinical study. We learn that dosing for subjects was increased for any given subject, where serum drug levels were used as a basis for stepping up the dose (where blinding was maintained by changing dose formulation for PLACEBO subjects). The DMC reviewed the efficacy data at various times (May 1979, April 1981, Oct. 1981), but it was not until Oct. 1981 that the DMC recommended stopping the trial for efficacy. What turned the tide was that the "monitoring boundary" had been crossed. (A full understanding of this particular case history requires an understanding of the O'Brien-Fleming procedure of monitoring boundaries, alpha values, the logrank statistic, Z value, and conditional power.) This case history also discloses the interesting fact-pattern where the DMC educated itself on results of a similar drug (the beta-blocker, timolol) for the same indication. We also learn that the consent form contained a clause on stopping for efficacy and for harm. This case history discloses the list of points in favor of stopping and points in favor of continuing the trial (the trial was stopped for efficacy).

This book clearly spells out many useful and subtle things useful to a trial manager or medical writer. Every case history provides a few unique take-home lessons. FIVE STARS.

First, I need to mention that I met the author about one year ago. We occasionally ride the train together, so when she mentioned she wrote a book I just had to read it.

I found this book to be very interesting. For instance, I learned that there are six different forms of energy and what they are. I also discovered that the usefulness of commercially available biomedical tools can sometimes be limited. These limits can be based on the type of study and also the ethnicity of the test subject. As a lay person I would not have expected ethnicity to affect the output of a monitoring tool. I was especially impressed with how innovative the author had to be when the usefulness of some of the commercially available biomedical tools used in the study fell short of their ability.

The author covered all her bases in the book, from selecting her subjects to accounting for the many variances in external factors that could affect the results. This text is thorough and typical in the clinical sense and the book is well researched. The appendix is chock full of supporting study materials.

From my point of view, this book is geared to a target audience. It would be a valuable resource to college students doing clinical work or someone who has an interest in how studies are done, such as researchers in any field. A doctorate student studying physiology would also benefit from this text.

I enjoyed the book and learned something from it and I'm not your typical audience for a text such as this. The mathematical data in the book is beyond my comprehension, so in essence I cannot comment or review on that data. However, the material I understood was without a doubt "5 stars."

If you're a juvenile defense attorney and actually want to litigate your cases -- get this book. Read it, keep re-reading it until you know it backwards and forwards. It comes with a CD in the back of it -- which has, among other things, the JACI (juvenile adjudicative competence interview) -- I have emailed this interview to my experts and ordered them to use it with my clients. The JACI breaks down questions according to the standard set forth in the Dusky and Godinez cases. There's also a legal companion. (separately purchased) It's ok, but the clinical book (this one) is the real jewel...

[...]In the prosecutor's guide, they MISQUOTE this book, and will use its distortions against you. Read the book, and you'll be ready in court. Isn't that what it's all about?

This book assists in the challenge to court appointed psychologists' reports and opinions, which have traditionally been accepted by defense lawyers without question. When the court appointed psychologist says that your client is competent, what do you do? This book helps you answer this question, and allows you to give the judge reasons to reject the psychologist's opinion and NOT rubber stamp the proceedings. I urge all of you to stop believing all of those court appointed evaluators at face value and take a closer look at juvenile competency.

This book is the most informative resource for any one in clinical research. I recommend it for Investigators, clinical nurse coordinators, administrators and anyone else who deals with sponsor drug companies, IRB's and Human Subjects. I found this book to be full of every detail I needed to become a responsible and ethical clinical research nurse. It has helped me coordinate my staffs activities and resources by providing guidelines that are understandable and easily followed. With this book your research team is on the path to success!