Life Expectancy for U.S. Women Heading Down?

In a previous post I predicted that U.S. life expectancies will peak soon and begin to go down by 2020. This process has already begun, for U.S. women. A report this month in Health Affairs offered this chilling announcement:

We examined trends in male and female mortality rates from 1992–96 to 2002–06 in 3,140 US counties. We found that female mortality rates increased in 42.8 percent of counties, while male mortality rates increased in only 3.4 percent. 

This is not the first study of its kind to report such a result. The New York Times devoted a story to the decline in female life expectancies last September (wherein it quoted from an August 2012 Health Affairs piece), and in June 2011 a far more extensive report appeared in Population Health Metrics, with similar findings. Even before that, a 2008 PLoS report by researchers from Harvard, U.C. San Francisco, and the University of Washington found life expectancy for U.S. women "began to level off or even decline in the 1980s for 4 percent of men and 19 percent of women." Bottom line, this is a process that started many years ago, and it has been verified repeatedly by different teams of researchers.

Counties in which female life expectancy is heading down are shown in red.

Some of the decline in life expectancy has been linked to educational level. In 1990, the difference in life expectancy between the most educated white females and the least educated was about 2 years. Now it's 10.4 years. No one has explained why lack of education should be deadlier today than in 1990. It's true that less-educated women smoke more tobacco than better-educated women, but that was true in 1990 as well. And anyway, in order to explain a life-expectancy delta of 10.4 years, one hundred percent of less-educated women would have to smoke, and one hundred percent of educated women would have to be lifetime non-smokers. Which is pretty far from the case.

Some experts have tried to pin the blame on rising obesity, but this is likely a red herring as well. For example, obesity rates for women barely changed from 1999 to 2010. It's interesting to note, too, that obesity is more prevalent among Hispanic women than non-Hispanic white women (by a solid margin) and yet life expectancy for Hispanic U.S. females is 83.7 years (CDC data), far higher than the national average (for U.S. women) of 81.1 years.

What's changed for women in the last 30 years? In a macro sense, the biggest change is that they've entered the workforce in huge numbers. Female participation in the labor force went from under 40% in 1960 to just over 60% in 1997 (where it's stayed ever since). It stands to reason that if you acquire the lifestyle habits of men (such as working outside the home every day), you'll perhaps be exposed to the same stressors that men are exposed to and acquire some of the same mortality risks. Especially if you're working harder, for less money.

Also, a variety of sources say that women suffer depression at twice the rate of men. Why is this important? Because mental illness is associated with higher mortality.

Finally, many people consider access to health care a women's issue. For example, women earn less than men yet pay more for health care. If women have poorer access to health care than men, this could partly explain the deterioration in female life expectancy.

There are no doubt other factors to consider. The greater question is whether the number of counties in which female life expectancy is on the decline will continue to grow until it includes nearly every county in the U.S., or whether the current trend represents a demographic split of some kind (between the well-educated and the low-educated, or between high earners and low earners). It also remains to be seen whether male life expectancies will also soon start to go down across the country. I suspect we'll see some interesting demographic trends soon, showing white Americans to be doing particularly poorly compared to non-whites. (Blacks and Hispanics are still making strong life-expectancy gains.) Time will tell.

Placebo Surgery

Stop me if you've heard this one.

In 1939, before there were drugs for angina pectoris, Italian surgeon David Fieschi developed a surgical technique for improving the outcomes of angina patients. The technique was called mammary ligation. It involved tying off the internal thoracic artery, which is a paired artery (one on each side of the sternum) supplying blood to the anterior chest wall and breasts, as a way of forcing additional blood to go to the heart. By the 1950s, Fieschi's operation was a mainline surgical intervention for angina, with success rates of 80% to 85%.

But in the late 1950s, two teams of surgeons (in Kansas City and Seattle) decided to do a sneaky bit of testing. They divided their angina surgery patients into a placebo group and a treatment group. The treatment group got the full mammary ligation. The placebo subjects were cut open under general anasthesia, their internal thoracic arteries exposed; and then they were sewn shut.

The published results were as remarkable as they were controversial. The treatment group's success rate was 73%, whereas the success rate among patients who got the sham surgery was 83%. See Cobb et al., New England Journal of Medicine, 1959 May 28;260(22):1115-8 and Dimond et al., American Journal of Cardiology, April 1960;5(4):483-486.

Patients in the sham group were quite convinced they were cured. One said: "I can do anything except real hard lifting. I am running farm equipment and maybe using one nitro a week. I used to need fifteen a day. Believe me, I'm cured."

The Cobb and Dimond mammary ligation studies show better than any drug study just how powerful the placebo effect can be. Angina is potentially debilitating. Yet the placebo effect brought pain down to manageable levels in people who had sham surgery, 80+ percent of the time. Is it any wonder acupuncture works for so many people? Or hypnosis? Or Prozac, Paxil, Celexa, Zoloft, Effexor, and all the rest?

For more on sham surgeries, see this 2006 paper. and this paper from 2011.

The Open-Source 3D-Printed Gun

An interesting experiment in democracy is underway. Texas gunsmith and crypto-anarchist Cody Wilson is spearheading an effort to design, and open-source the plans for, the first 3D-printable gun. Earlier this month, Wilson's nonprofit organization, Defense Distributed, released a video showing a semi-automatic rifle firing off over 600 rounds with a printed plastic lower receiver.

I'm not a firearms enthusiast, but I'm a democracy enthusiast and an admirer of the crypto-anarchist style (things like Wikileaks), so this particular experiment in 1st and 2nd Amendment rights has me captivated, not the less so because Mr. Wilson himself is a law student.

I admit a certain fascination with the technological challenges presented by 3D gun-printing. The common presumption seems to be that a plastic gun will never be practicable (because a plastic barrel will never be able to withstand the temperatures and pressures achieved in conventional firearms operation), hence we needn't fear that the Cody Wilsons of the world will get very far in their quest for a 3D-printed weapon. We can reject that notion outright, it seems to me. Wilson will eventually succeed. The only question is how much technological innovation he'll have to bring to bear on the problem.

There's a long history to improvisational firearms (zip guns and such) in this country, and the fact is, if all you want to do is discharge a store-bought 9mm round from a tube, you can do so with $2 worth of off-the-shelf parts today (see http://www.gunssavelife.com/?p=5235 for demo).

Cody Wilson's effort to create a printable gun is a technologically naive approach, in the sense that Wilson has chosen to replicate an existing design in plastic, rather than look at this as a clean-sheet-of-paper problem. I know nothing about guns, yet it seems obvious to me that any kind of firearm is a complete system that requires more than a sum-of-the-parts approach. If the goal is to deliver a conventional bullet of a certain caliber out of the end of a barrel at a certain muzzle velocity, it seems to me you'd want to design the gun from the barrel back rather than from the stock up, so to speak.

This AR15 lower receiver was printed using an
old-school Stratsys 3D printer and $30 worth of resin.

Having said this, I have zero doubt that a plastic barrel can be developed to fire a standard round of one sort or another. The question is whether such a barrel can do it more than one time.

A precedent for what Wilson is doing exists in the attempts to make a plastic car engine. Polimotor Research took the bottom-up approach when it made its famed plastic engine for Ford in the 1980s. It started with "bottom end" parts (oil pan, block, valve covers, etc.), progressing to connecting rods, pushrods, etc., but then hit the wall (technologically) when it got to the high-temperature components: pistons, cylinder liners, and valves, all of which had to remain metallic. I foresee something similar happening with the Wilson gun. When it comes to designing a plastic barrel that can accommodate a conventional round, Wilson will run into an impedance mismatch (so to speak) that will require some original thinking.

Increasing the barrel-wall thickness (probably to an inch or more) may well keep the barrel from shattering, but the question is what the inside of the barrel is going to look like after pressures of 20,000+ psi and temperatures of several thousand degrees Fahrenheit. (Note: Had Wilson decided to clone something simpler, like a 38 Smith & Wesson, the max pressure would be only 14,500 psi. See this chart.) These pressures and temperatures exist for only a fraction of a second, and only in the first inch or so of bullet travel, so perhaps Wilson can design a multi-part barrel in which the first two inches are metal, or in which the first two-inch segment is a disposable plastic piece (replaced after every round). Or perhaps Wilson can produce an innovation in barrel design that, by clever use of gas plenums and pneumatic oscillator effects, shapes the pressure and temperature curves exactly as needed, in operation. If Wilson were to design his own round, further innovations could be attempted, but I'm assuming Wilson's goal is to produce a gun that fires off-the-shelf ammunition. That certainly seems to be what he's after.

Bottom line, there are technical challenges ahead, requiring more than mere reverse engineering to solve. But I think the challenges can be overcome.

As for the non-technical challenges (e.g., to 1st and 2nd Amendment law), Wilson is doing us a service, I think, by accelerating the debate on guns and gun laws in this country. What will it mean to be able to "print" your own gun? Will the gun-control debate turn into a printer-control debate? Will gun laws become ammunition laws? (Clearly, you won't be able to 3D-print gunpowder. Wilson's gun needs real ammo.) Will we be any worse off, as a society, when anyone with a printer can print handguns and semi-automatic weapons? Or are we already so saturated  with firearms that it won't matter?

One wonders what the Founding Fathers would have written, in place of the Second Amendment, if they had known about 3D printer technology. Perhaps: "The right of the people to keep and bear printers shall not be infringed"?

A Call for Mandatory Publishing of Clinical Trials

Non-publication of research is a huge problem in medicine, specifically in drug trials. It's a problem that affects all of us: health care consumers and health care providers, young, old, and in between.

Of all the clinical trials that are conducted and completed, only around half get published in academic journals. Trials with positive results are twice as likely to be published as others. This is according to a systematic review conducted in 2010 by the NHS NIHR Health Technology Assessment Programme (UK).

Studies have repeatedly found Data from http://www.alltrials.net/wp-content/uploads/2013/01/Missing-trials-briefing-note.pdf

Selective publication of results is, of course, antithetical to the spirit of good science. It also has serious practical consequences. Clinicians who rely on published findings to determine which medications to dispense (and how best to manage their use) end up recommending drugs without knowing what their real effects are. As one physician, Dr. Richard Lehman, puts it: "It is a scandal that doctors like myself often prescribe treatments without knowing their true benefits and harms because research evidence from human trials has been withheld. That means that over my 35 years as a GP, I have unintentionally spent large sums of [government] money on treatments that did not work, and some patients have suffered avoidable harm. We need immediate access to all the data relating to all the drugs and devices which we use on millions of people every day."

Fortunately, there's a move afoot to get this situation corrected. All Trials Registered, All Results Reported is an initiative of Sense About Science, Bad Science, BMJ, James Lind Initiative, the Centre for Evidence-based Medicine and others aimed at getting 100% of clinical-trials research published. The group started a petition drive in January (you can sign the AllTrials petition here; and be sure to Tweet it with hashtag #AllTrials), and it has begun to get some traction in the industry. GlaxoSmithKline got behind the AllTrials campaign in February, saying it would publish all of its clinical trial data going back to the formation of GSK in 2000 when it merged with SmithKline Beecham. Roche, on the other hand, made the mistake of issuing a feel-good press release saying it supports greater transparency in clinical trials while sticking to its position of not releasing trial data.

For more on this story, or to sign the petition, go to alltrials.net, and to donate, go to http://www.justgiving.com/alltrials/eurl.axd/2fb898db34ec76479ab47c6c24a9eeb0. And please, spread the word to your social media contacts. This is a matter of importance to anyone who takes medicine.

77 Poor-Quality Antidepressant Studies

Everyone who tries to become better informed about the science behind psychiatric medications sooner or later has to deal with a rather large and frustrating problem, which is that the published scientific literature on commercial drugs is spotty in quality and of dubious reliability. I've mentioned before the excellent 2005 paper on PLoS called "Why Most Published Research Findings Are False," by Dr. John P. A. Ioannidis. Interested readers will also want to consult a 2010 Atlantic article called "Lies, Damned Lies, and Medical Science," and this recent (and extensive) British analysis of bias in the scientific literature. These works mostly deal with publication bias (selective publication of studies and results), but the problems with medical research go much deeper than that. Some of the problems have to do with things like study design, but there are also deep ethical issues around ghostwriting and guest authorship, undisclosed conflicts of interest, and other issues that generally aren't issues in other realms of science, such as (say) theoretical physics.

It helps, when reading papers, to have degrees in science (which I do), but even then it can be tricky to tell a reliable paper from a not-so-reliable paper. Which is why I'm glad I stumbled across Gartlehner G, et al., (2011) "Second-Generation Antidepressants in the Pharmacologic Treatment of Adult Depression: An Update of the 2007 Comparative Effectiveness Review," Rockville (MD): Agency for Healthcare Research and Quality (US); 2011 Dec. (Comparative Effectiveness Reviews, No. 46.) In Appendix D of this 954-page book there's a detailed listing, prepared by the report's 13 authors on behalf of the U.S. Dept. of Health and Human Services, of 77 scientific papers (all having to do with second-generation antidepressants) that were found to be of "poor quality." I've reproduced that listing here. Full references are given further below. Item [1] in the list of references is a paper on how "poor quality" is determined. Papers [2] through [78] are the actual 77 scientific papers that were found to be of poor quality.

I decided to reproduce the list here as a kind of note-to-self that I can refer back to later, when I'm reading some of the papers, but also as a reminder to myself and others that the literature surrounding many of the latest drugs for the treatment of depression is basically not to be taken at face value. All scientific literature (in all fields) needs to be viewed critically. That's not the issue. The issue is that the scientific literature surrounding psychiatric drugs is particularly treacherous.

Which drugs do the 77 papers talk about? They all refer to one or more of the medications shown in this table:

Generic Name	U.S. Trade Name
Bupropion	Wellbutrin®; Wellbutrin SR®; Wellbutrin XL®
Citalopram	Celexa®
Desvenlafaxine	Pristiq®
Duloxetine	Cymbalta®
Escitalopram	Lexapro®
Fluoxetine	Prozac®; Prozac Weekly®
Fluvoxamine	Luvox®
Mirtazapine	Remeron® Remeron Sol tab®
Nefazodone	Serzone®
Paroxetine	Paxil®; Paxil CR®
Sertraline	Zoloft®
Trazodone	Desyrel®
Venlafaxine	Effexor®; Effexor XR®

These drugs represent some of the most popular medications in America today. All of these drugs are approved for use in treatment of depression except for Luvox, which is widely prescribed off-label for depression. (The only approved use of Luvox is for OCD.)

In the table immediately below, ITT refers to "intention to treat" analysis; LTF refers to loss to followup bias; RCT means randomized controlled trial. Numbers in brackets refer to the citations given further below.

Study	Design	Reason(s) for Poor Quality Rating
Aguglia et al., 1993 [2]	RCT	High LTF
Amini et al., 2005 [3]	RCT	No ITT analysis
Ashman et al., 2009 [4]	RCT	No ITT analysis
Brown, et al., 2005 [5]	RCT	No ITT analysis
Byerley, et al., 1988 [6]	RCT	No ITT analysis
Claghorn, 1992 [7]	RCT	No ITT analysis
Claghorn, et al., 1996 [8]	RCT	High LTF and no ITT analysis
Claghorn &Lesem, 1995 [9]	RCT	High LTF
Clerc et al., 1994 [10]	RCT	High differential attrition
Cohn, et al., 1990 [11]	RCT	No ITT analysis
Cohn & Wilcox, 1992 [12]	RCT	No ITT analysis
Corrigan, et al., 2000 [13]	RCT	High differential attrition
Croft, et al., 2002 [14]	RCT	High LTF
Dube, et al., 2010 [15]	RCT	High LTF
Dunbar, et al., 1993 [16]	RCT	No ITT analysis
Dunbar, et al., 1991 [17]	RCT	High LTF
Elliott, et al., 1998 [18]	RCT	High LTF
Evans, et al., 1997 [19]	RCT	High LTF
Fabre, et al., 1996 [20]	RCT	High LTF
Fabre, 1992 [21]	RCT	High differential attrition
Fabre, et al., 1995 [22]	RCT	High LTF
Fabre & Putman, 1987 [23]	RCT	High LTF
Falk et al., 1989 [24]	RCT	High LTF
Fava, et al., 1997 [25]	RCT	No ITT analysis
Fava, et al., 2005 [26]	RCT	High LTF
Feighner, et al., 1998 [27]	RCT	High LTF
Feighner, 1992 [28]	RCT	High LTF
Feighner;Boyer, 1992 [29]	RCT	High LTF
Feighner, et al., 1993 [30]	RCT	High LTF
Ferrando et al., 1997 [31]	RCT	No ITT analysis
Flament & Lane, 2001 [32]	RCT	No ITT analysis
Garakani et al., 2008 [33]	RCT	No ITT analysis
Gastpar et al., 2006 [34]	RCT	No ITT analysis
Goldstein et al., 2004 [35]	RCT	High LTF
Grigoriadis et al., 2003 [36]	Observational	No ITT analysis
Gülseren et al., 2005 [37]	RCT	No ITT analysis
Hegerl, et al., 2010 [38]	RCT	High attrition
Kasper, et al., 2010 [39]	Pooled analysis	No systematic literature search
Lapierre, et al., 1987 [40]	RCT	No ITT analysis
March, et al., 1990 [41]	RCT	No ITT analysis
McGrath, et al., 2000 [42]	RCT	High differential attrition
Mesters et al., 1993 [43]	RCT	No ITT analysis
Montgomery et al., 2007 [44] Montgomery, et al., 2008 [45]	Systematic Review	Publication bias
Muijen, et al., 1988 [46]	RCT	No ITT analysis
Nyth, et al., 1992 [47]	RCT	No ITT analysis
Oslin et al., 2003 [48]	RCT	High attrition
Petracca, et al., 2001 [49]	RCT	No ITT analysis
Pettinati, et al., 2010 [50]	RCT	High attrition
Ravindran, et al., 1995 [51]	RCT	High attrition
Reimherr, et al., 1998 [52]	RCT	High attrition
Rickels, et al., 1992 [53]	RCT	No ITT analysis
Rickels and Case, 1982 [54]	RCT	No ITT analysis
Rickels, et al., 1994 [55]	RCT	High attrition, no ITT
Roscoe et al., 2005 [56]	RCT	No ITT analysis
Rosenbaum et al., 1998 [57]	Observational	No ITT analysis
Roth, et al., 1990 [58]	RCT	No ITT analysis
Roy-Byrne, et al., 2000 [59]	RCT	High attrition
Rudolph, et al., 1998 [60]	RCT	High attrition
Schmitz et al., 2001 [61]	RCT	High LTF
Schweizer, et al., 1991 [62]	RCT	High attrition
Smith & Glaudin, 1992 [63]	RCT	High attrition
Smith, et al., 1990 [64]	RCT	High attrition
Spielmans, 2008 [65]	Systematic Review	No quality assessment of included studies, lack of clear and comprehensive search strategy
Stahl et al., 2000 [66]	RCT	High attrition
Thase et al., 2001 [67]	Pooled analysis	No systematic literature search
Thase et al., 2006 [68]	RCT	High LTF
Tollefson et al., 1994 [69] Beasley et al., 1991 [70]	Meta-analysis	No systematic literature search
Trkulja, 2010 [71]	RCT	No dual literature review
Vartiainen & Leinonen, 1994 [72]	RCT	High attrition, no ITT
Wade et al., 2003 [73]	RCT	High LTF
Wagner et al., 1998 [74]	RCT	No ITT analysis
Weintraub, et al., 2010 [75]		High attrition and imputations
Wernicke, et al., 1987 [76]	RCT	No ITT analysis
Winokur et al., 2003 [77]	RCT	No ITT analysis
Zanardi et al., 1996 [78]	RCT	High LTF

ITT, intent to treat analysis; LTF, loss to followup; RCT, randomized controlled trial. For more on these terms, see [1] below.

References: The List of 77 Poor-Quality Studies

NOTE: The first paper below is not one of the poor-quality studies; it is a paper on how to determine if studies are of poor quality. Citations 2 through 78 constitute the "poor-quality studies."

1. Owens DK, Lohr KN, Atkins D, et al. AHRQ series paper 5: grading the strength of a body of evidence when comparing medical interventions--agency for healthcare research and quality and the effective health-care program. J Clin Epidemiol. 2010 May;63(5):513–23. [PubMed]

 

2. Aguglia E, Casacchia M, Cassano GB, et al. Double-blind study of the efficacy and safety of sertraline versus fluoxetine in major depression. Int Clin Psychopharmacol. 1993 Fall;8(3):197–202. [PubMed]

 

3. Amini H, Aghayan S, Jalili SA, et al. Comparison of mirtazapine and fluoxetine in the treatment of major depressive disorder: a double-blind, randomized trial. J Clin Pharm Ther. 2005 Apr;30(2):133–8. [PubMed]

 

4. Ashman TA, Cantor JB, Gordon WA, et al. A randomized controlled trial of sertraline for the treatment of depression in persons with traumatic brain injury. Arch Phys Med Rehabil. 2009;90(5):733–40. [PubMed]

 

5. Brown ES, Vigil L, Khan DA, et al. A randomized trial of citalopram versus placebo in outpatients with asthma and major depressive disorder: a proof of concept study. Biol Psychiatry. 2005 Dec 1;58(11):865–70. [PubMed]

 

6. Byerley WF, Reimherr FW, Wood DR, et al. Fluoxetine, a selective serotonin uptake inhibitor, for the treatment of outpatients with major depression. J Clin Psychopharmacol. 1988 Apr;8(2):112–5. [PubMed]

 

7. Claghorn JL. The safety and efficacy of paroxetine compared with placebo in a double-blind trial of depressed outpatients. J Clin Psychiatry. 1992 Feb;53(Suppl):33–5. [PubMed]

 

8. Claghorn JL, Earl CQ, Walczak DD, et al. Fluvoxamine maleate in the treatment of depression: a single-center, double-blind, placebo-controlled comparison with imipramine in outpatients. J Clin Psychopharmacol. 1996 Apr;16(2):113–20. [PubMed]

 

9. Claghorn JL, Lesem MD. A double-blind placebo-controlled study of Org 3770 in depressed outpatients. J Affect Disord. 1995 Jun 8;34(3):165–71. [PubMed]

 

10. Clerc GE, Ruimy P, Verdeau-Palles J. A double-blind comparison of venlafaxine and fluoxetine in patients hospitalized for major depression and melancholia. The Venlafaxine French Inpatient Study Group. Int Clin Psychopharmacol. 1994 Sep;9(3):139–43. [PubMed]

 

11. Cohn JB, Crowder JE, Wilcox CS, et al. A placebo- and imipramine-controlled study of paroxetine.Psychopharmacol Bull. 1990;26(2):185–9. [PubMed]

 

12. Cohn JB, Wilcox CS. Paroxetine in major depression: a double-blind trial with imipramine and placebo. J Clin Psychiatry. 1992 Feb;53(Suppl):52–6. [PubMed]

 

13. Corrigan MH, Denahan AQ, Wright CE, et al. Comparison of pramipexole, fluoxetine, and placebo in patients with major depression. Depress Anxiety. 2000;11(2):58–65. [PubMed]

 

14. Croft H, Houser TL, Jamerson BD, et al. Effect on body weight of bupropion sustained-release in patients with major depression treated for 52 weeks. Clin Ther. 2002 Apr;24(4):662–72. [PubMed]

 

15. Dube S, Dellva MA, Jones M, et al. A study of the effects of LY2216684, a selective norepinephrine reuptake inhibitor, in the treatment of major depression. J Psychiatr Res. 2010;44(6):356–63. [PubMed]

 

16. Dunbar GC, Claghorn JL, Kiev A, et al. A comparison of paroxetine and placebo in depressed outpatients. Acta Psychiatr Scand. 1993 May;87(5):302–5. [PubMed]

 

17. Dunbar GC, Cohn JB, Fabre LF, et al. A comparison of paroxetine, imipramine and placebo in depressed out-patients. Br J Psychiatry. 1991 Sep;159:394–8. [PubMed]

 

18. Elliott AJ, Uldall KK, Bergam K, et al. Randomized, placebo-controlled trial of paroxetine versus imipramine in depressed HIV-positive outpatients. Am J Psychiatry. 1998 Mar;155(3):367–72. [PubMed]

 

19. Evans M, Hammond M, Wilson K, et al. Placebo-controlled treatment trial of depression in elderly physically ill patients. Int J Geriatr Psychiatry. 1997 Aug;12(8):817–24. [PubMed]

 

20. Fabre L, Birkhimer LJ, Zaborny BA, et al. Fluvoxamine versus imipramine and placebo: a double-blind comparison in depressed patients. Int Clin Psychopharmacol. 1996 Jun;11(2):119–27. [PubMed]

 

21. Fabre LF. A 6-week, double-blind trial of paroxetine, imipramine, and placebo in depressed outpatients. J Clin Psychiatry. 1992 Feb;53(Suppl):40–3. [PubMed]

 

22. Fabre LF, Abuzzahab FS, Amin M, et al. Sertraline safety and efficacy in major depression: a double-blind fixed-dose comparison with placebo. Biol Psychiatry. 1995 Nov 1;38(9):592–602. [PubMed]

 

23. Fabre LF, Putman HP 3rd. A fixed-dose clinical trial of fluoxetine in outpatients with major depression. J Clin Psychiatry. 1987 Oct;48(10):406–8. [PubMed]

 

24. Falk WE, Rosenbaum JF, Otto MW, et al. Fluoxetine versus trazodone in depressed geriatric patients. J Geriatr Psychiatry Neurol. 1989 Oct-Dec;2(4):208–14. [PubMed]

 

25. Fava M, Mulroy R, Alpert J, et al. Emergence of adverse events following discontinuation of treatment with extended-release venlafaxine. Am J Psychiatry. 1997 Dec;154(12):1760–2. [PubMed]

 

26. Fava M, Alpert J, Nierenberg AA, et al. A Double-blind, randomized trial of St John's wort, fluoxetine, and placebo in major depressive disorder. J Clin Psychopharmacol. 2005 Oct;25(5):441–7. [PubMed]

 

27. Feighner J, Targum SD, Bennett ME, et al. A double-blind, placebo-controlled trial of nefazodone in the treatment of patients hospitalized for major depression. J Clin Psychiatry. 1998 May;59(5):246–53. [PubMed]

 

28. Feighner JP. A double-blind comparison of paroxetine, imipramine and placebo in depressed outpatients. Int Clin Psychopharmacol. 1992 Jun;6 Suppl 4:31–5. [PubMed]

 

29. Feighner JP, Boyer WF. Paroxetine in the treatment of depression: a comparison with imipramine and placebo. J Clin Psychiatry. 1992 Feb;53(Suppl):44–7. [PubMed]

 

30. Feighner JP, Cohn JB, Fabre LF Jr, et al. A study comparing paroxetine placebo and imipramine in depressed patients. J Affect Disord. 1993 Jun;28(2):71–9. [PubMed]

 

31. Ferrando SJ, Goldman JD, Charness WE. Selective serotonin reuptake inhibitor treatment of depression in symptomatic HIV infection and AIDS. Improvements in affective and somatic symptoms. Gen Hosp Psychiatry.1997 Mar;19(2):89–97. [PubMed]

 

32. Flament MF, Lane R. Acute antidepressant response to fluoxetine and sertraline in psychiatric outpatients with psychomotor agitation. International Journal of Psychiatry in Clinical Practice. 2001;5(2):103–9.

 

33. Garakani A, Martinez JM, Marcus S, et al. A randomized, double-blind, and placebo-controlled trial of quetiapine augmentation of fluoxetine in major depressive disorder. Int Clin Psychopharmacol. 2008;23(5):269–75. [PubMed]

 

34. Gastpar M, Singer A, Zeller K. Comparative efficacy and safety of a once-daily dosage of hypericum extract STW3-VI and citalopram in patients with moderate depression: a double-blind, randomised, multicentre, placebo-controlled study. Pharmacopsychiatry. 2006;39(2):66–75. [PubMed]

 

35. Goldstein DJ, Lu Y, Detke MJ, et al. Duloxetine in the treatment of depression: a double-blind placebo-controlled comparison with paroxetine. J Clin Psychopharmacol. 2004 Aug;24(4):389–99. [PubMed]

 

36. Grigoriadis S, Kennedy SH, Bagby RM. A comparison of antidepressant response in younger and older women. J Clin Psychopharmacol. 2003 Aug;23(4):405–7. [PubMed]

 

37. Gulseren L, Gulseren S, Hekimsoy Z, et al. Comparison of fluoxetine and paroxetine in type II diabetes mellitus patients. Arch Med Res. 2005 Mar-Apr;36(2):159–65. [PubMed]

 

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