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24 abril, 2013

MBE | Bases of evidence based medicine

English: German Network for Evidence Based Medicine Deutsch: Deutsches Netzwerk Evidenzbasierte Medizin (Photo credit: Wikipedia)

MBE | Bases of evidence based medicine
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Authors: Martín Muñoz P¹, González de Dios J²
¹Director de Unidad Clínica en Atención Primaria, CS La Plata. Hospital Universitario Virgen del Rocío. Sevilla. Sevilla (España). ²Departamento de Pediatría. Hospital General Universitario de Alicante. (España).

Correspondence: Pedro Martín Muñoz. Email: pedromartinm@telefonica.net

Palabras clave: práctica clínica basada en la evidencia; medicina basada en pruebas; guías de práctica clínica

Keywords: evidence-based practice; evidence-based medicine; clinical practice guidelines

Publication date: 01/09/2010

De la evidencia a la recomendación: una tarea pendiente

Una aspiración irrenunciable de la medicina actual, reclamada por todos sus protagonistas (enfermos, profesionales y administraciones), es que los actos médicos se sustenten en conocimientos científicos obtenidos de procesos de investigación clínica rigurosa. Decidir si una intervención clínica resulta adecuada para un paciente determinado equivale a establecer si existe un grado razonable de certeza de que el balance entre los beneficios, por un lado, y los riesgos, los inconvenientes y los costes, por el otro, de dicha intervención resulta lo suficientemente favorable como para que merezca la pena aplicarla. Los conceptos de calidad (nivel) de la evidencia yfuerza (grado) de las recomendaciones constituyen un pilar fundamental de la práctica basada en la evidencia, en su intento por estandarizar y proporcionar a los clínicos reglas para analizar la literatura científica, determinar su validez y considerar su utilidad en la asistencia sanitaria.

Cada vez toma más cuerpo el tomar decisiones médicas que estén fundamentadas en el mejor nivel de evidencia (indica hasta qué punto nuestra confianza en la estimación de un efecto es adecuada para apoyar una recomendación) y la mayor fuerza de recomendación (indica hasta qué punto podemos confiar si poner en práctica la recomendación conllevará más beneficios que riesgos).

La calidad (nivel) de evidencia se ha relacionado, generalmente, con el diseño del estudio (estudios descriptivos o analíticos, observacionales o experimentales) y la calidad de los mismos. La meta de la investigación es la agudeza en la medición, lo que implica precisión (limitar el error aleatorio) y validez (limitar el error sistemático). En este sentido, por las características propias de cada diseño, el “nivel” de evidencia será mayor en los estudios analíticos que en los descriptivos, y superior en los estudios experimentales (ejemplo, ensayo clínico) que en los observacionales (ejemplo, estudios de cohortes y estudios de casos y controles). Sin embargo, no toda pregunta clínica se puede abordar con el mismo diseño científico: el ensayo clínico es el patrón oro para intervenciones terapéuticas, pero no será el diseño apropiado para preguntas sobre diagnóstico o pronóstico.

Se establecen unos criterios de calidad propios para cada tipo de diseño. Así, podemos considerar cinco criterios de calidad en el ensayo clínico (definición clara de la población de estudio, intervención y resultado de interés; correcta aleatorización; adecuado enmascaramiento; seguimiento completo - menos del 20% de pérdidas -; análisis correcto - análisis por intención de tratar y control de covariables no equilibradas con la aleatorización -), que serán diferentes a los criterios de calidad barajados en el caso de estudios de valoración de pruebas diagnósticas (comparación con un patrón de referencia válido; muestra representativa; descripción completa de los métodos de realización de la prueba diagnóstica; control de sesgos - comparación ciega e independiente -; control de sesgos de incorporación, verificación diagnóstica y revisión; análisis correcto - datos que permitan calcular indicadores de validez -) o de cohortes (cohortes representativas de la población con y sin exposición, libres del efecto o enfermedad de interés; medición independiente, ciega y válida de exposición y efecto; seguimiento suficiente - superior al 80% -, completo y no diferencial; control de la relación temporal de los acontecimientos – exposición/efecto - y de la relación entre nivel de exposición y grado de efecto - dosis/respuesta -; análisis correcto - control de factores de confusión y modificadores de efecto -), por ejemplo.

La fuerza (grado) de las recomendaciones indica hasta qué punto podemos confiar en que poner en práctica la recomendación conllevará más beneficio que riesgo. En la elaboración de las recomendaciones se debe tener en cuenta, en primer lugar, el nivel de evidencia, pero también otras consideraciones: balance entre beneficios y riesgos, consistencia de los estudios, aplicabilidad práctica en mi paciente o población (incluyendo el riesgo basal en mi población), valores y preferencias de la población diana a la cual va dirigida, costes, etc. Establecer una recomendación, a favor o en contra de una intervención, no significa que todos los pacientes deban ser tratados de la misma manera, pues en la toma de decisión la evidencia procedente de la investigación es sólo uno de los cuatro círculos en una toma de decisiones basada en pruebas (figura 1).

Figura 1. Modelo actualizado en la toma de decisiones basada en pruebas. Mostrar/ocultar

Ambos conceptos, aunque relacionados y complementarios, se ocupan de aspectos distintos. Aunque la fuerza de una recomendación se apoya, decisivamente, en la calidad de la evidencia que la sustenta, ello puede no resultar suficiente de ser por ejemplo muy pequeña la magnitud del efecto sobre las variables primarias, tener poca precisión la estimación realizada o ser irrelevante desde el punto de vista clínico el resultado medido (diferencia entre significación estadística e importancia clínica). Por último, el elemento clave para decidir el grado de recomendación se obtiene al considerar el binomio beneficio/perjuicio neto para la salud, consecuencia del análisis de varios factores (magnitud del efecto y daño, disponibilidad social y coste).

El primer intento serio de introducir rigor y transparencia en la jerarquización de la evidencia fue realizado hace ya más de 30 años por la Canadian Task Force on Preventive Health Care (CTFPHC)1, adaptado posteriormente por la United State Preventive Services Task Force (USPSTF)2. Desde entonces numerosas organizaciones e instituciones, entre las que destacan el Centre for Evidence-Based Medicine (CEBM) de Oxford3, el Scottish Intercollegiate Guidelines Network (SIGN)4, el National Institute for Health and Clinical Excellence (NICE)5 o la U.S. Agency for Health Research and Quality (AHRQ)6, han ido desarrollando sus propios sistemas jerárquicos y, actualmente, se contabilizan más de cien herramientas, 19 sistemas para evaluar la calidad y 7 para graduar las recomendaciones7. En síntesis, las escalas pueden utilizar letras (ej. A, B, C, etc.), números (ej. I, II, III, etc.) o una combinación de ambos (ej. Ia, Ib, IIa, etc.). Sin embargo, la situación a la que se ha llegado dista de ser satisfactoria8,9. La comparación entre las distintas propuestas existentes (tabla 1) pone de manifiesto diferencias sustanciales en los criterios de gradación, con una baja sensibilidad y reproducibilidad de los mismos, múltiples posibilidades para evaluar y estructurar la evidencia y diferentes interpretaciones de los grados de recomendación. Además, la proliferación de escalas genera confusión y dudas en los usuarios, constatándose la inexistencia, hasta ese momento, de un modelo adecuado que pudiera ser universalmente aceptado10-12.

More information..

08 marzo, 2013

Evidence Based Medicine: what is it and what isn´t

English: German Network for Evidence Based Medicine Deutsch: Deutsches Netzwerk Evidenzbasierte Medizin (Photo credit: Wikipedia)

Evidence-based medicine (EBM) (sometimes called evidence-based health care or EBHC to broaden its application to allied health care professionals) has been defined as "the conscientious, explicit and judicious use of current best evidence in making decisions about the care of individual patients."^[1]^[2] Trisha Greenhalgh and Anna Donald define it more specifically as "the use of mathematical estimates of the risk of benefit and harm, derived from high-quality research on population samples, to inform clinical decision-making in the diagnosis, investigation or management of individual patients."^[3]
EBM seeks to assess the strength of the evidence of risks and benefits of treatments (including lack of treatment) and diagnostic tests.^[4] This helps clinicians predict whether a treatment will do more good than harm.^[5]
Evidence quality can be assessed based on the source type (from meta-analyses and systematic reviews of triple-blind randomized clinical trials with concealment of allocation and no attrition at the top end, down to conventional wisdom at the bottom), as well as other factors including statistical validity, clinical relevance, currency, and peer-review acceptance. EBM recognizes that many aspects of health care depend on individual factors such as quality- and value-of-life judgments, which are only partially subject to quantitative scientific methods. Application of EBM data therefore depends on patient circumstances and preferences, and medical treatment remains subject to input from personal, political, philosophical, ethical, economic, and esthetic values.
Because EBM is used in allied fields, including dentistry, nursing and psychology, evidence-based practice (EBP) is a more encompassing term.

07 octubre, 2011

Routine HIV Screening — What Counts in Evidence-Based Policy?

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Routine HIV Screening — What Counts in Evidence-Based Policy?

Ronald Bayer, Ph.D., and Gerald M. Oppenheimer, Ph.D., M.P.H.

N Engl J Med 2011; 365:1265-1268October 6, 2011

Article
References: In January 2011, the President's Advisory Council on HIV/AIDS called on the U.S. Preventive Services Task Force (USPSTF) to reconsider its 2005 determination that the scientific evidence did not justify routine testing for human immunodeficiency virus (HIV) in adolescents and adults in the general U.S. population. In July, the Institute of Medicine issued a report calling for annual HIV screening in all sexually active women. These are the most recent episodes in a struggle that began in 2006, when the Centers for Disease Control and Prevention (CDC) recommended routine HIV testing. Normally, USPSTF decisions receive little attention. Sometimes, however — for example, when the Task Force recommended against routine mammography for women in their 40s — there is political fallout, and observers question what kind of evidence should count and who should make those determinations. The battle over HIV screening, though less public and heated than the mammography debate, demonstrates how the same evidence can lead the country's top public health agency and the body charged by the government with providing scientifically grounded recommendations on clinical preventive interventions to reach dramatically different conclusions.
The USPSTF reflects the legacy of British clinician Archie Cochrane, who criticized medicine for failing to systematically weigh clinical and epidemiologic evidence in making health care decisions. Established in 1984 and sponsored by the Agency for Health Care Research and Quality since 1998, the Task Force evaluates clinical preventive services on the basis of systematic reviews of empirical evidence, determining the magnitude of benefits and harms and issuing grades ranging from A, strongly recommended, to D, not recommended. Capturing the Task Force's ethos, Mark Helfand of the Oregon Evidence-based Practice Center said, “It is never rational to say we must do something [now] because it will take too long to get the evidence. Such actions time and again have been wrong.”
In 2005, the Task Force concluded that although “targeted [HIV] screening misses a substantial proportion of HIV positive patients . . . universal screening would result in large numbers of patients screened for each clinical outcome prevented.”1 Regarding the potential effects of identifying many more people who were unaware of being HIV-positive, the Task Force declared, “Despite evidence that knowledge of HIV positive status reduces some high risk behaviors, there is insufficient evidence with which to accurately estimate the effects on transmission.” Given the potential benefits and harms associated with HIV diagnosis, “including fears of rejection, abandonment, verbal abuse and physical assault,” the Task Force gave general HIV screening a C rating, indicating no recommendation for or against. By stating that individual physicians should determine whether to test, the Task Force rejected the notion of making HIV testing routine practice.
In a published exchange encapsulating the ensuing debate about what evidence regarding HIV testing should be required for changing public policy, a group of clinicians with expertise in AIDS wrote that the benefits of expanding routine HIV testing were “unmistakable.”2 Knowledge of infection provided an opportunity to prevent transmission. Claiming that the potential harms of HIV screening were “minimal,” they argued that the risks did not warrant the withholding of testing. Pointing to current practices' failure to meet the public health and clinical challenges posed by HIV, they concluded, “We cannot allow ineffective testing policies to be perpetuated when experience demonstrates that change is required.”
The chair of the Task Force responded by reemphasizing the burdens of testing for individual patients and clinicians and declaring that as many as 11,000 non–high-risk patients would have to be screened over 3 years to prevent one clinical progression to death. Given the limited duration of primary care visits and what he characterized as the very small likelihood that “any one clinician would provide health benefits to an otherwise undetected seropositive patient,” he concluded that “the physician should consider whether this time might be better spent providing other preventive services that carry the potential to improve outcomes for more patients.”
In September 2006, the CDC issued new recommendations for routine screening that differed sharply from those of the Task Force.3 Haunted by the persistent failure to diagnose HIV in the 250,000-plus people in this country who are infected but unidentified (see tableEstimated Number of People in the United States 13 Years of Age or Older Living with HIV Infection and Number and Percentage Whose HIV Infection was Undiagnosed, 2008.), and on the basis of its own data analysis, the CDC concluded that the public health benefit of reduced transmission justified a departure from its own prior guidance. In fact, it asserted that infected people who were ignorant of their status were a public health hazard, contributing disproportionately to HIV's spread. Citing a recent meta-analysis, the CDC found evidence that people who were aware of their HIV infection substantially curtailed their high-risk behaviors.
The crafters of the new recommendations rejected the Task Force analysis, arguing that an analysis of risk and burden focused on each individual screened ignores significant likely benefits at the population level. The question was what course to pursue when evidence did not meet the most exacting scientific standards. Not taking action, permitting an ineffective policy to persist, was in fact an action. As Bernard Branson of the CDC Division of HIV/AIDS Prevention noted, “The Task Force has the luxury of making no recommendation for or against. The CDC does not really have that option.”
Although the USPSTF usually doesn't revisit its determinations for 5 years, considerable pressure and claims about new evidence led to a “focused update” in April 2007.4 Yet it didn't modify the earlier conclusion.
After examining the nature of the evidence used by the CDC and what it considered methodologic flaws in relevant studies, the USPSTF concluded that the CDC had overstated routine HIV testing's potential effects on transmission. The Task Force also acknowledged the difficulty of obtaining the evidence it deemed crucial: “Studies directly linking screening to decreased rates of transmission would require very large populations with long duration of follow up and are difficult to perform. Not surprisingly no such studies have been published since [the] 2005 evidence synthesis was completed.”
And there the issue remained, despite a 2009 analysis by the American College of Physicians and the HIV Medicine Association supporting the CDC recommendation for routine testing.5 Ironically, what rekindled consideration in 2010 was not new evidence, but the passage of the Affordable Care Act (ACA), which requires health plans to cover preventive services, without charge to patients, if they've received an A or B rating from the USPSTF. Routine HIV screening would thus remain uncovered. In response to that ACA requirement, the Institute of Medicine Committee on Preventive Series for Women recommended that annual HIV screening be included among covered services. Furthermore, 2009 recommendations by the U.S. Public Health Service that antiretroviral therapy be initiated earlier underscored the clinical importance of identifying persons with asymptomatic HIV infection, and in 2011, the HIV Prevention Trials Network's HPTN052 trial demonstrated the powerful effect of therapy on transmission rates.
The Task Force is revisiting its 2005 determination and may reach a decision by the end of 2011. But this saga underscores a broader matter of critical importance to anyone committed to evidence-based practice in medicine and public health. What is from one perspective methodologic rigor may be viewed by others with public health responsibilities as methodologic zealotry. An emphasis on the importance of contextual flexibility is to some an invitation to perilous inconsistency.
Public health practitioners confront the challenge of choosing policies to pursue in the face of uncertainty. Such decisions must take account of the severity of the potential harms from action or inaction. Certainly, such determinations require a strong evidence base, but they will be different for those whose first priority is scientific exactitude and those who focus on making policy in the context of public health, where a precautionary perspective mandates action to prevent foreseeable harms, even when the evidence does not meet the most rigorous demands of science.
Disclosure forms provided by the authors are available with the full text of this article at NEJM.org.
This article (10.1056/NEJMp1108657) was published on September 21, 2011, at NEJM.org.
SOURCE INFORMATION
From the Center for the History and Ethics of Public Health, Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York.