Re: Why Most Published Research Findings Are False

January 21, 2006

>>Why most published research findings are false.

Including the results/conslusions and findings of this stidy also.

January 21, 2006

>>Why most published research findings are false.

Including the results/conslusions and findings of this stidy also.

January 21, 2006

Thanks for the brilliant insight Jeff!! And I don't mean that tongue in cheek.

What then can we depend on for unbiased, accurate info, if not peer reviewed scientific studies?? Seems silly to me to say that MOST (probably some, but not most) studies are false.

on 1/21/2006 8:29 AM, Jeff Novick at jnovick@... wrote:

>>Why most published research findings are false.

Including the results/conslusions and findings of this stidy also.

January 21, 2006

Thanks for the brilliant insight Jeff!! And I don't mean that tongue in cheek.

What then can we depend on for unbiased, accurate info, if not peer reviewed scientific studies?? Seems silly to me to say that MOST (probably some, but not most) studies are false.

on 1/21/2006 8:29 AM, Jeff Novick at jnovick@... wrote:

>>Why most published research findings are false.

Including the results/conslusions and findings of this stidy also.

January 21, 2006

This article is free full text at:

http://www.pubmedcentral.gov/articlerender.fcgi?tool=pubmed & pubmedid=16060722

and don't forget Simpsons rule.

To me a finding is not scientifically correct if it does not fit every case. It's merely statisical.

Anecdotal evidence often doesn't agree.

"How Can We Improve the Situation?

Is it unavoidable that most research findings are false, or can we improve the situation? A major problem is that it is impossible to know with 100% certainty what the truth is in any research question. In this regard, the pure “gold” standard is unattainable. "

If you're really worried:

Ioannidis JP, Haidich AB, Lau J. Any casualties in the clash of randomised and observational evidence? BMJ. 2001;322:879–880. [Free Full text in PMC]

http://www.pubmedcentral.gov/articlerender.fcgi?artid=1120057

Benson K, Hartz AJ. A comparison of observational studies and randomized, controlled trials. N Engl J Med. 2000;342:1878–1886. [PubMed] [Free Full Text]

Concato J, Shah N, Horwitz RI. Randomized, controlled trials, observational studies,

and the hierarchy of research designs. N Engl J Med. 2000;342:1887–1892. [PubMed] [Free Full Text]

Ioannidis JPA, Cappelleri JC, Lau J. Issues in the comparisons of meta-analysis and large trials. JAMA. 1998;281:1089–1093.

Pocock SJ, Elbourne DR. Randomized trials or observational tribulations?

N Engl J Med. 2000;342:1907–1909. [PubMed] [Full Text]

Lau J, Ioannidis JPA, Schmid CH. Summing up evidence: one answer is not always enough. Lancet. 1998;351:123–127. [PubMed] [Full Text]

Alpha-Tocopherol, Beta Carotene Cancer Prevention Study Group. The effect of vitamin E and beta carotene on the incidence of lung cancer and other cancers in male smokers. N Engl J Med. 1994;330:1029–1035. [PubMed] [Free Full Text]

Yusuf S, Dagenais G, Pogue J, Bosch J, Sleight P. Vitamin E supplementation and cardiovascular events in high risk patients. The Heart Outcomes Prevention Evaluation Study Investigators. N Engl J Med. 2000;342:154–160. [PubMed] [Free Full Text]

Lawlor DA, Davey G, Kundu D, Bruckdorfer KR, Ebrahim S. Those confounded vitamins:

What can we learn from the differences between observational versus randomised trial evidence?

Lancet. 2004;363:1724–1727. [PubMed] [Full Text]

Vandenbroucke JP. When are observational studies as credible as randomised trials?

Lancet. 2004;363:1728–1731. [PubMed] [Full Text]

Michiels S, Koscielny S, Hill C. Prediction of cancer outcome with microarrays:

A multiple random validation strategy. Lancet. 2005;365:488–492. [PubMed] [Full Text]

Ioannidis JPA, Ntzani EE, Trikalinos TA, Contopoulos-Ioannidis DG. Replication validity of genetic association studies.

Nat Genet. 2001;29:306–309. [PubMed] [Full Text]

Colhoun HM, McKeigue PM, Davey G. Problems of reporting genetic associations with complex outcomes.

Lancet. 2003;361:865–872. [PubMed] [Full Text]

Ioannidis JP. Genetic associations: False or true?

Trends Mol Med. 2003;9:135–138. [PubMed] [Full Text]

Ioannidis JPA. Microarrays and molecular research: Noise discovery?

Lancet. 2005;365:454–455. [PubMed] [Full Text]

Sterne JA, Davey G. Sifting the evidence—What's wrong with significance tests.

BMJ. 2001;322:226–231. [Free Full text in PMC]

Wacholder S, Chanock S, -Closas M, Elghormli L, Rothman N. Assessing the probability

that a positive report is false: An approach for molecular epidemiology studies.

J Natl Cancer Inst. 2004;96:434–442. [PubMed] [Free Full Text]

Risch NJ. Searching for genetic determinants in the new millennium.

Nature. 2000;405:847–856. [PubMed] [Full Text]

Kelsey, JL.; Whittemore, AS.; , AS.; , WD.

Methods in observational epidemiology, 2nd ed. New York: Oxford U Press; 1996. 432 pp.

Topol EJ. Failing the public health—Rofecoxib, Merck, and the FDA.

N Engl J Med. 2004;351:1707–1709. [PubMed] [Full Text]

Yusuf S, R, Peto R. Why do we need some large, simple randomized trials?

Stat Med. 1984;3:409–422. [PubMed]

Altman DG, Royston P. What do we mean by validating a prognostic model?

Stat Med. 2000;19:453–473. [PubMed] [Full Text]

Taubes G. Epidemiology faces its limits.

Science. 1995;269:164–169. [PubMed]

Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, et al. Molecular classification of cancer:

Class discovery and class prediction by gene expression monitoring.

Science. 1999;286:531–537. [PubMed] [Full Text]

Moher D, Schulz KF, Altman DG. The CONSORT statement: Revised recommendations for

improving the quality of reports of parallel-group randomised trials.

Lancet. 2001;357:1191–1194. [PubMed] [Full Text]

Ioannidis JP, SJ, Gotzsche PC, O'Neill RT, Altman DG, et al. Better reporting of harms in randomized trials:

An extension of the CONSORT statement.

Ann Intern Med. 2004;141:781–788. [PubMed] [Free Full Text]

International Conference on Harmonisation E9 Expert Working Group. ICH Harmonised Tripartite Guideline.

Statistical principles for clinical trials.

Stat Med. 1999;18:1905–1942. [PubMed]

Moher D, Cook DJ, Eastwood S, Olkin I, Rennie D, et al. Improving the quality of reports of

meta-analyses of randomised controlled trials: The QUOROM statement. Quality of Reporting of Meta-analyses.

Lancet. 1999;354:1896–1900. [PubMed] [Full Text]

Stroup DF, Berlin JA, Morton SC, Olkin I, on GD, et al. Meta-analysis of observational

studies in epidemiology: A proposal for reporting. Meta-analysis of Observational Studies in Epidemiology (MOOSE) group.

JAMA. 2000;283:2008–2012. [PubMed] [Free Full Text]

Marshall M, Lockwood A, Bradley C, C, Joy C, et al. Unpublished rating scales:

A major source of bias in randomised controlled trials of treatments for schizophrenia.

Br J Psychiatry. 2000;176:249–252. [PubMed] [Free Full Text]

Altman DG, Goodman SN. Transfer of technology from statistical journals to the biomedical literature.

Past trends and future predictions.

JAMA. 1994;272:129–132. [PubMed]

Chan AW, Hrobjartsson A, Haahr MT, Gotzsche PC, Altman DG. Empirical evidence for selective

reporting of outcomes in randomized trials: Comparison of protocols to published articles.

JAMA. 2004;291:2457–2465. [PubMed] [Free Full Text]

Krimsky S, Rothenberg LS, Stott P, G. Scientific journals and their authors' financial interests: A pilot study.

Psychother Psychosom. 1998;67:194–201. [PubMed] [Full Text]

Papanikolaou GN, Baltogianni MS, Contopoulos-Ioannidis DG, Haidich AB, kakis IA, et al.

Reporting of conflicts of interest in guidelines of preventive and therapeutic interventions.

BMC Med Res Methodol. 2001;1:3. [Free Full text in PMC]

Antman EM, Lau J, Kupelnick B, Mosteller F, Chalmers TC. A comparison of results of meta-analyses

of randomized control trials and recommendations of clinical experts. Treatments for myocardial infarction.

JAMA. 1992;268:240–248. [PubMed]

Ioannidis JP, Trikalinos TA. Early extreme contradictory estimates may appear in published research:

The Proteus phenomenon in molecular genetics research and randomized trials.

J Clin Epidemiol. 2005;58:543–549. [PubMed] [Full Text]

Ntzani EE, Ioannidis JP. Predictive ability of DNA microarrays for cancer outcomes and correlates:

An empirical assessment.

Lancet. 2003;362:1439–1444. [PubMed] [Full Text]

Ransohoff DF. Rules of evidence for cancer molecular-marker discovery and validation.

Nat Rev Cancer. 2004;4:309–314. [PubMed] [Full Text]

Lindley DV. A statistical paradox. Biometrika. 1957;44:187–192.

Bartlett MS. A comment on D.V. Lindley's statistical paradox.

Biometrika. 1957;44:533–534.

Senn SJ. Two cheers for P-values.

J Epidemiol Biostat. 2001;6:193–204. [PubMed]

De Angelis C, Drazen JM, Frizelle FA, Haug C, Hoey J, et al. Clinical trial registration:

A statement from the International Committee of Medical Journal Editors.

N Engl J Med. 2004;351:1250–1251. [PubMed] [Full Text]

Ioannidis JPA. Contradicted and initially stronger effects in highly cited clinical research.

JAMA. 2005;294:218–228. [PubMed] [Free Full Text]

Hsueh HM, Chen JJ, Kodell RL. Comparison of methods for estimating the number of true null hypotheses in multiplicity testing.

J Biopharm Stat. 2003;13:675–689. [PubMed]

Regards.

[ ] Why Most Published Research Findings Are False

PLoS Med. 2005 Aug;2(8):e124. Epub 2005 Aug 30. Why most published research findings are false.Ioannidis JP.Department of Hygiene and Epidemiology, University ofIoannina School of Medicine, Ioannina, Greece.jioannid@...There is increasing concern that most currentpublished research findings are false. The probabilitythat a research claim is true may depend on studypower and bias, the number of other studies on thesame question, and, importantly, the ratio of true tono relationships among the relationships probed ineach scientific field. In this framework, a researchfinding is less likely to be true when the studiesconducted in a field are smaller; when effect sizesare smaller; when there is a greater number and lesserpreselection of tested relationships; where there isgreater flexibility in designs, definitions, outcomes,and analytical modes; when there is greater financialand other interest and prejudice; and when more teamsare involved in a scientific field in chase ofstatistical significance. Simulations show that formost study designs and settings, it is more likely fora research claim to be false than true. Moreover, formany current scientific fields, claimed researchfindings may often be simply accurate measures of theprevailing bias. In this essay, I discuss theimplications of these problems for the conduct andinterpretation of research.PMID: 16060722 [PubMed - in process]

January 21, 2006

This article is free full text at:

http://www.pubmedcentral.gov/articlerender.fcgi?tool=pubmed & pubmedid=16060722

and don't forget Simpsons rule.

To me a finding is not scientifically correct if it does not fit every case. It's merely statisical.

Anecdotal evidence often doesn't agree.

"How Can We Improve the Situation?

Is it unavoidable that most research findings are false, or can we improve the situation? A major problem is that it is impossible to know with 100% certainty what the truth is in any research question. In this regard, the pure “gold” standard is unattainable. "

If you're really worried:

Ioannidis JP, Haidich AB, Lau J. Any casualties in the clash of randomised and observational evidence? BMJ. 2001;322:879–880. [Free Full text in PMC]

http://www.pubmedcentral.gov/articlerender.fcgi?artid=1120057

Benson K, Hartz AJ. A comparison of observational studies and randomized, controlled trials. N Engl J Med. 2000;342:1878–1886. [PubMed] [Free Full Text]

Concato J, Shah N, Horwitz RI. Randomized, controlled trials, observational studies,

and the hierarchy of research designs. N Engl J Med. 2000;342:1887–1892. [PubMed] [Free Full Text]

Ioannidis JPA, Cappelleri JC, Lau J. Issues in the comparisons of meta-analysis and large trials. JAMA. 1998;281:1089–1093.

Pocock SJ, Elbourne DR. Randomized trials or observational tribulations?

N Engl J Med. 2000;342:1907–1909. [PubMed] [Full Text]

Lau J, Ioannidis JPA, Schmid CH. Summing up evidence: one answer is not always enough. Lancet. 1998;351:123–127. [PubMed] [Full Text]

Alpha-Tocopherol, Beta Carotene Cancer Prevention Study Group. The effect of vitamin E and beta carotene on the incidence of lung cancer and other cancers in male smokers. N Engl J Med. 1994;330:1029–1035. [PubMed] [Free Full Text]

Yusuf S, Dagenais G, Pogue J, Bosch J, Sleight P. Vitamin E supplementation and cardiovascular events in high risk patients. The Heart Outcomes Prevention Evaluation Study Investigators. N Engl J Med. 2000;342:154–160. [PubMed] [Free Full Text]

Lawlor DA, Davey G, Kundu D, Bruckdorfer KR, Ebrahim S. Those confounded vitamins:

What can we learn from the differences between observational versus randomised trial evidence?

Lancet. 2004;363:1724–1727. [PubMed] [Full Text]

Vandenbroucke JP. When are observational studies as credible as randomised trials?

Lancet. 2004;363:1728–1731. [PubMed] [Full Text]

Michiels S, Koscielny S, Hill C. Prediction of cancer outcome with microarrays:

A multiple random validation strategy. Lancet. 2005;365:488–492. [PubMed] [Full Text]

Ioannidis JPA, Ntzani EE, Trikalinos TA, Contopoulos-Ioannidis DG. Replication validity of genetic association studies.

Nat Genet. 2001;29:306–309. [PubMed] [Full Text]

Colhoun HM, McKeigue PM, Davey G. Problems of reporting genetic associations with complex outcomes.

Lancet. 2003;361:865–872. [PubMed] [Full Text]

Ioannidis JP. Genetic associations: False or true?

Trends Mol Med. 2003;9:135–138. [PubMed] [Full Text]

Ioannidis JPA. Microarrays and molecular research: Noise discovery?

Lancet. 2005;365:454–455. [PubMed] [Full Text]

Sterne JA, Davey G. Sifting the evidence—What's wrong with significance tests.

BMJ. 2001;322:226–231. [Free Full text in PMC]

Wacholder S, Chanock S, -Closas M, Elghormli L, Rothman N. Assessing the probability

that a positive report is false: An approach for molecular epidemiology studies.

J Natl Cancer Inst. 2004;96:434–442. [PubMed] [Free Full Text]

Risch NJ. Searching for genetic determinants in the new millennium.

Nature. 2000;405:847–856. [PubMed] [Full Text]

Kelsey, JL.; Whittemore, AS.; , AS.; , WD.

Methods in observational epidemiology, 2nd ed. New York: Oxford U Press; 1996. 432 pp.

Topol EJ. Failing the public health—Rofecoxib, Merck, and the FDA.

N Engl J Med. 2004;351:1707–1709. [PubMed] [Full Text]

Yusuf S, R, Peto R. Why do we need some large, simple randomized trials?

Stat Med. 1984;3:409–422. [PubMed]

Altman DG, Royston P. What do we mean by validating a prognostic model?

Stat Med. 2000;19:453–473. [PubMed] [Full Text]

Taubes G. Epidemiology faces its limits.

Science. 1995;269:164–169. [PubMed]

Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, et al. Molecular classification of cancer:

Class discovery and class prediction by gene expression monitoring.

Science. 1999;286:531–537. [PubMed] [Full Text]

Moher D, Schulz KF, Altman DG. The CONSORT statement: Revised recommendations for

improving the quality of reports of parallel-group randomised trials.

Lancet. 2001;357:1191–1194. [PubMed] [Full Text]

Ioannidis JP, SJ, Gotzsche PC, O'Neill RT, Altman DG, et al. Better reporting of harms in randomized trials:

An extension of the CONSORT statement.

Ann Intern Med. 2004;141:781–788. [PubMed] [Free Full Text]

International Conference on Harmonisation E9 Expert Working Group. ICH Harmonised Tripartite Guideline.

Statistical principles for clinical trials.

Stat Med. 1999;18:1905–1942. [PubMed]

Moher D, Cook DJ, Eastwood S, Olkin I, Rennie D, et al. Improving the quality of reports of

meta-analyses of randomised controlled trials: The QUOROM statement. Quality of Reporting of Meta-analyses.

Lancet. 1999;354:1896–1900. [PubMed] [Full Text]

Stroup DF, Berlin JA, Morton SC, Olkin I, on GD, et al. Meta-analysis of observational

studies in epidemiology: A proposal for reporting. Meta-analysis of Observational Studies in Epidemiology (MOOSE) group.

JAMA. 2000;283:2008–2012. [PubMed] [Free Full Text]

Marshall M, Lockwood A, Bradley C, C, Joy C, et al. Unpublished rating scales:

A major source of bias in randomised controlled trials of treatments for schizophrenia.

Br J Psychiatry. 2000;176:249–252. [PubMed] [Free Full Text]

Altman DG, Goodman SN. Transfer of technology from statistical journals to the biomedical literature.

Past trends and future predictions.

JAMA. 1994;272:129–132. [PubMed]

Chan AW, Hrobjartsson A, Haahr MT, Gotzsche PC, Altman DG. Empirical evidence for selective

reporting of outcomes in randomized trials: Comparison of protocols to published articles.

JAMA. 2004;291:2457–2465. [PubMed] [Free Full Text]

Krimsky S, Rothenberg LS, Stott P, G. Scientific journals and their authors' financial interests: A pilot study.

Psychother Psychosom. 1998;67:194–201. [PubMed] [Full Text]

Papanikolaou GN, Baltogianni MS, Contopoulos-Ioannidis DG, Haidich AB, kakis IA, et al.

Reporting of conflicts of interest in guidelines of preventive and therapeutic interventions.

BMC Med Res Methodol. 2001;1:3. [Free Full text in PMC]

Antman EM, Lau J, Kupelnick B, Mosteller F, Chalmers TC. A comparison of results of meta-analyses

of randomized control trials and recommendations of clinical experts. Treatments for myocardial infarction.

JAMA. 1992;268:240–248. [PubMed]

Ioannidis JP, Trikalinos TA. Early extreme contradictory estimates may appear in published research:

The Proteus phenomenon in molecular genetics research and randomized trials.

J Clin Epidemiol. 2005;58:543–549. [PubMed] [Full Text]

Ntzani EE, Ioannidis JP. Predictive ability of DNA microarrays for cancer outcomes and correlates:

An empirical assessment.

Lancet. 2003;362:1439–1444. [PubMed] [Full Text]

Ransohoff DF. Rules of evidence for cancer molecular-marker discovery and validation.

Nat Rev Cancer. 2004;4:309–314. [PubMed] [Full Text]

Lindley DV. A statistical paradox. Biometrika. 1957;44:187–192.

Bartlett MS. A comment on D.V. Lindley's statistical paradox.

Biometrika. 1957;44:533–534.

Senn SJ. Two cheers for P-values.

J Epidemiol Biostat. 2001;6:193–204. [PubMed]

De Angelis C, Drazen JM, Frizelle FA, Haug C, Hoey J, et al. Clinical trial registration:

A statement from the International Committee of Medical Journal Editors.

N Engl J Med. 2004;351:1250–1251. [PubMed] [Full Text]

Ioannidis JPA. Contradicted and initially stronger effects in highly cited clinical research.

JAMA. 2005;294:218–228. [PubMed] [Free Full Text]

Hsueh HM, Chen JJ, Kodell RL. Comparison of methods for estimating the number of true null hypotheses in multiplicity testing.

J Biopharm Stat. 2003;13:675–689. [PubMed]

Regards.

[ ] Why Most Published Research Findings Are False

PLoS Med. 2005 Aug;2(8):e124. Epub 2005 Aug 30. Why most published research findings are false.Ioannidis JP.Department of Hygiene and Epidemiology, University ofIoannina School of Medicine, Ioannina, Greece.jioannid@...There is increasing concern that most currentpublished research findings are false. The probabilitythat a research claim is true may depend on studypower and bias, the number of other studies on thesame question, and, importantly, the ratio of true tono relationships among the relationships probed ineach scientific field. In this framework, a researchfinding is less likely to be true when the studiesconducted in a field are smaller; when effect sizesare smaller; when there is a greater number and lesserpreselection of tested relationships; where there isgreater flexibility in designs, definitions, outcomes,and analytical modes; when there is greater financialand other interest and prejudice; and when more teamsare involved in a scientific field in chase ofstatistical significance. Simulations show that formost study designs and settings, it is more likely fora research claim to be false than true. Moreover, formany current scientific fields, claimed researchfindings may often be simply accurate measures of theprevailing bias. In this essay, I discuss theimplications of these problems for the conduct andinterpretation of research.PMID: 16060722 [PubMed - in process]

January 21, 2006

I have to disagree " that it's not scientifically correct... [if]it's

merely statiscal. " Merely? Statistics is the basis for modern

physics. And it's not scientific? Here's Hawking on the

point.

" Thus it seems Einstein was doubly wrong when he said, God does not

play dice. Not only does God definitely play dice, but He sometimes

confuses us by throwing them where they can't be seen.

" Many scientists are like Einstein, in that they have a deep

emotional attachment to determinism. Unlike Einstein, they have

accepted the reduction in our ability to predict, that quantum

theory brought about. But that was far enough. They didn't like the

further reduction, which black holes seemed to imply. They have

therefore claimed that information is not really lost down black

holes. But they have not managed to find any mechanism that would

return the information. It is just a pious hope that the universe is

deterministic, in the way that Laplace thought. I feel these

scientists have not learnt the lesson of history. The universe does

not behave according to our pre-conceived ideas. It continues to

surprise us. "

http://www.hawking.org.uk/lectures/dice.html

Mike

--- In , " jwwright " <jwwright@e...>

wrote:

>

> This article is free full text at:

> http://www.pubmedcentral.gov/articlerender.fcgi?

tool=pubmed & pubmedid=16060722

> and don't forget Simpsons rule.

> To me a finding is not scientifically correct if it does not fit

every case. It's merely statisical.

> Anecdotal evidence often doesn't agree.

>

> " How Can We Improve the Situation?

>

> Is it unavoidable that most research findings are false, or can we

improve the situation? A major problem is that it is impossible to

know with 100% certainty what the truth is in any research question.

In this regard, the pure " gold " standard is unattainable. "

>

> If you're really worried:

>

> a.. Ioannidis JP, Haidich AB, Lau J. Any casualties in the clash

of randomised and observational evidence? BMJ. 2001;322:879-880.

[Free Full text in PMC]

> http://www.pubmedcentral.gov/articlerender.fcgi?artid=1120057

>

> Benson K, Hartz AJ. A comparison of observational studies and

randomized, controlled trials. N Engl J Med. 2000;342:1878-1886.

[PubMed] [Free Full Text]

>

> Concato J, Shah N, Horwitz RI. Randomized, controlled trials,

observational studies,

> and the hierarchy of research designs. N Engl J Med. 2000;342:1887-

1892. [PubMed] [Free Full Text]

>

> Ioannidis JPA, Cappelleri JC, Lau J. Issues in the comparisons of

meta-analysis and large trials. JAMA. 1998;281:1089-1093.

>

> Pocock SJ, Elbourne DR. Randomized trials or observational

tribulations?

> N Engl J Med. 2000;342:1907-1909. [PubMed] [Full Text]

>

> Lau J, Ioannidis JPA, Schmid CH. Summing up evidence: one answer

is not always enough. Lancet. 1998;351:123-127. [PubMed] [Full Text]

>

> Alpha-Tocopherol, Beta Carotene Cancer Prevention Study Group. The

effect of vitamin E and beta carotene on the incidence of lung

cancer and other cancers in male smokers. N Engl J Med.

1994;330:1029-1035. [PubMed] [Free Full Text]

>

> Yusuf S, Dagenais G, Pogue J, Bosch J, Sleight P. Vitamin E

supplementation and cardiovascular events in high risk patients. The

Heart Outcomes Prevention Evaluation Study Investigators. N Engl J

Med. 2000;342:154-160. [PubMed] [Free Full Text]

>

> Lawlor DA, Davey G, Kundu D, Bruckdorfer KR, Ebrahim S.

Those confounded vitamins:

> What can we learn from the differences between observational

versus randomised trial evidence?

> Lancet. 2004;363:1724-1727. [PubMed] [Full Text]

>

> Vandenbroucke JP. When are observational studies as credible as

randomised trials?

> Lancet. 2004;363:1728-1731. [PubMed] [Full Text]

>

> Michiels S, Koscielny S, Hill C. Prediction of cancer outcome with

microarrays:

> A multiple random validation strategy. Lancet. 2005;365:488-492.

[PubMed] [Full Text]

>

> Ioannidis JPA, Ntzani EE, Trikalinos TA, Contopoulos-Ioannidis DG.

Replication validity of genetic association studies.

> Nat Genet. 2001;29:306-309. [PubMed] [Full Text]

>

> Colhoun HM, McKeigue PM, Davey G. Problems of reporting

genetic associations with complex outcomes.

> Lancet. 2003;361:865-872. [PubMed] [Full Text]

>

> Ioannidis JP. Genetic associations: False or true?

> Trends Mol Med. 2003;9:135-138. [PubMed] [Full Text]

>

> Ioannidis JPA. Microarrays and molecular research: Noise

discovery?

> Lancet. 2005;365:454-455. [PubMed] [Full Text]

>

> Sterne JA, Davey G. Sifting the evidence-What's wrong with

significance tests.

> BMJ. 2001;322:226-231. [Free Full text in PMC]

>

> Wacholder S, Chanock S, -Closas M, Elghormli L, Rothman N.

Assessing the probability

> that a positive report is false: An approach for molecular

epidemiology studies.

> J Natl Cancer Inst. 2004;96:434-442. [PubMed] [Free Full Text]

>

> Risch NJ. Searching for genetic determinants in the new

millennium.

> Nature. 2000;405:847-856. [PubMed] [Full Text]

>

> Kelsey, JL.; Whittemore, AS.; , AS.; , WD.

> Methods in observational epidemiology, 2nd ed. New York: Oxford U

Press; 1996. 432 pp.

>

> Topol EJ. Failing the public health-Rofecoxib, Merck, and the FDA.

> N Engl J Med. 2004;351:1707-1709. [PubMed] [Full Text]

>

> Yusuf S, R, Peto R. Why do we need some large, simple

randomized trials?

> Stat Med. 1984;3:409-422. [PubMed]

>

> Altman DG, Royston P. What do we mean by validating a prognostic

model?

> Stat Med. 2000;19:453-473. [PubMed] [Full Text]

>

> Taubes G. Epidemiology faces its limits.

> Science. 1995;269:164-169. [PubMed]

>

> Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, et al.

Molecular classification of cancer:

> Class discovery and class prediction by gene expression

monitoring.

> Science. 1999;286:531-537. [PubMed] [Full Text]

>

> Moher D, Schulz KF, Altman DG. The CONSORT statement: Revised

recommendations for

> improving the quality of reports of parallel-group randomised

trials.

> Lancet. 2001;357:1191-1194. [PubMed] [Full Text]

>

> Ioannidis JP, SJ, Gotzsche PC, O'Neill RT, Altman DG, et al.

Better reporting of harms in randomized trials:

> An extension of the CONSORT statement.

> Ann Intern Med. 2004;141:781-788. [PubMed] [Free Full Text]

>

> International Conference on Harmonisation E9 Expert Working Group.

ICH Harmonised Tripartite Guideline.

> Statistical principles for clinical trials.

> Stat Med. 1999;18:1905-1942. [PubMed]

>

> Moher D, Cook DJ, Eastwood S, Olkin I, Rennie D, et al. Improving

the quality of reports of

> meta-analyses of randomised controlled trials: The QUOROM

statement. Quality of Reporting of Meta-analyses.

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> Regards.

>

> [ ] Why Most Published Research Findings

Are False

>

> PLoS Med. 2005 Aug;2(8):e124. Epub 2005 Aug 30.

>

> Why most published research findings are false.

>

> Ioannidis JP.

>

> Department of Hygiene and Epidemiology, University of

> Ioannina School of Medicine, Ioannina, Greece.

> jioannid@c...

>

> There is increasing concern that most current

> published research findings are false. The probability

> that a research claim is true may depend on study

> power and bias, the number of other studies on the

> same question, and, importantly, the ratio of true to

> no relationships among the relationships probed in

> each scientific field. In this framework, a research

> finding is less likely to be true when the studies

> conducted in a field are smaller; when effect sizes

> are smaller; when there is a greater number and lesser

> preselection of tested relationships; where there is

> greater flexibility in designs, definitions, outcomes,

> and analytical modes; when there is greater financial

> and other interest and prejudice; and when more teams

> are involved in a scientific field in chase of

> statistical significance. Simulations show that for

> most study designs and settings, it is more likely for

> a research claim to be false than true. Moreover, for

> many current scientific fields, claimed research

> findings may often be simply accurate measures of the

> prevailing bias. In this essay, I discuss the

> implications of these problems for the conduct and

> interpretation of research.

>

> PMID: 16060722 [PubMed - in process]

>

January 21, 2006