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Enregistrement W1998151345 · doi:10.7326/0003-4819-138-8-200304150-00018

When To Start Therapy for HIV Infection: A Swinging Pendulum in Search of Data

2003· letter· en· W1998151345 sur OpenAlexaboutno aff
H. Clifford Lane, James D. Neaton

Notice bibliographique

RevueAnnals of Internal Medicine · 2003
Typeletter
Langueen
DomaineImmunology and Microbiology
ThématiqueHIV Research and Treatment
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineHuman immunodeficiency virus (HIV)VirologyIntensive care medicine

Résumé

récupéré en direct d'OpenAlex

Editorials15 April 2003When To Start Therapy for HIV Infection: A Swinging Pendulum in Search of DataFREEH. Clifford Lane, MD and James D. Neaton, PhDH. Clifford Lane, MDFrom National Institute of Allergy and Infectious Diseases; National Institutes of Health, Bethesda, MD; and University of Minnesota; Minneapolis, MN 55414. and James D. Neaton, PhDFrom National Institute of Allergy and Infectious Diseases; National Institutes of Health, Bethesda, MD; and University of Minnesota; Minneapolis, MN 55414.Author, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-138-8-200304150-00018 SectionsAboutVisual AbstractPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Among the fundamental questions that need to be addressed regarding the treatment of patients with HIV infection are the strategy questions of when to start therapy, what therapy to start, and when to change therapy. The current inability to eradicate HIV, which has led to a need for long-term therapeutic strategies, and the increased recognition of long-term drug toxicities have made these questions compelling. Unfortunately, the answers remain unclear.Over the past 7 years, in the absence of definitive evidence, several professional societies and governmental entities have provided guidelines for the initiation of antiretroviral therapy (ART). These organizations have suggested guidelines that deal with a wide range of issuesfrom the treatment of all patients with viral loads greater than 10 000 copies/mL (1) to the more recent recommendation to definitely begin therapy only in patients with CD4+ T-cell counts less than 0.200 109 cells/L. Guidelines for the best approach to patients with CD4+ T-cell counts between 0.200 and 0.350 109 cells/L remain uncertain (2). As stated in the most recent edition of the guidelines from the U.S. Department of Health and Human Services and the Henry J. Kaiser Family Foundation (3), While randomized clinical trials provide strong evidence for treating patients with <200 CD4+ T cells/mm3, the optimal time to initiate antiretroviral therapy among asymptomatic patients with CD4+ T-cell counts > 200 cells/mm3 is not known. Unfortunately, this swing in the pendulum of expert opinion from early, aggressive therapy to a more cautious approach was not concluded from data derived from randomized trials with clinical outcomes. It was due to the influence of data from observational studies, case reports, and short-term trials that showed unexpected toxicities associated with treatment and little evidence that earlier intervention had any impact on progression to AIDS (4-9).The study by Palella and colleagues in this issue (10) attempts to swing the pendulum back toward earlier intervention. This analysis of data from 1994 to 2002 from the Centers for Disease Control and Preventionsponsored HIV Outpatient Study (HOPS) observational cohort divided patients into groups based on CD4+ T-cell count (0.201 to 0.350 109 cells/L, 0.351 to 0.500 109 cells/L, and 0.501 to 0.750 109 cells/L). The investigators compared mortality rates of patients who began ART in their initial CD4+ T-cell group with those of patients who deferred therapy until their CD4+ T-cell count declined to a lower group. For patients with initial CD4+ T-cell counts between 0.201 and 0.350 109 cells/L, initiating therapy at this time rather than waiting until CD4+ T-cell counts declined to less than 0.201 109 cells/L was associated with reduced mortality (15.4 vs. 56.4 deaths/1000 person-years, respectively; P < 0.001).The work of Palella and colleagues is unique compared with other recent reports on this topic (4-7) because the authors compared survival for participants who began ART in a specific CD4+ group with that of participants in the same group who deferred treatment until their CD4+ T-cell counts declined to a lower CD4+ group. In contrast, other studies typically classified participants by CD4+ T-cell count at the time of initiation of treatment and thus compared risk for AIDS or death on the basis of CD4+ group at the time of initiation of therapy. By starting the clock at the same time for those who initiated and those who deferred therapy, Palella and colleagues overcame one of the problems of using observational data to decide when to start ART. However, like the other reports, these comparisons may be subject to confounding. Although Palella and colleagues adjusted for many potentially confounding variables (age, sex, race, insurance status, viral load at time of first ART, receipt of highly active antiretroviral therapy [HAART], and CD4+ T-cell count at time of first observation within each subgroup), the decision to start treatment probably involved several additional factors related to prognosis.As the authors point out, another important limitation relates to statistical power. Overall, a total of only 53 end points (deaths) occurred during the follow-up period. Even for the subgroup that formed the basis for their main conclusion, the 399 participants in the 0.201 to 0.350 109 cells/L subgroup, the distribution of the 33 end points, once adjusted for known confounding variables, did not achieve statistical significance (hazard ratio, 0.57; P = 0.16). To directly address the question of whether to defer therapy in patients with CD4+ T-cell counts greater than 0.200 109 cells/L would require a randomized trial of considerable size. For example, a study of treatment-naive patients with CD4+ T-cell counts greater than 0.250 109 cells/L, randomly assigned to immediate or deferred therapy, would require 650 events to show a 20% difference in mortality between groups with 80% power. At a rate of progression of 1% per year, 65 000 patient-years of follow-up or a study of 6500 patients for 10 years would be required. While studies of this size exist in other areas (11, 12), they are the exception in HIV research.We applaud Palella and colleagues' novel approach to observational data; however, because of potential confounding factors and limited power, their data are unlikely to change current recommendations about when to initiate therapy. These data do, however, generate new uncertainty in this area and may motivate the design and conduct of trials that will contribute to this important debate. As one views the global epidemic of HIV infection and the vast numbers of untreated patients, one also sees opportunities to perform studies that involve large sample sizes and that require long-term follow-up. The questions regarding treatment strategy are equally pressing and important for developed and developing countries. In developing countries, these questions can be addressed in a way that is consistent with the ethical principles of clinical research (13, 14) and that helps to develop the infrastructure required for delivery of state-of-the art care to patients with HIV infection. Our enthusiasm to test the newest class of drugs, such as entry or integrase inhibitors, must be balanced by a need to define better strategies for the use of existing drugs.References1. Carpenter CC, Fischl MA, Hammer SM, Hirsch MS, Jacobsen DM, Katzenstein DA, . Antiretroviral therapy for HIV infection in 1997. Updated recommendations of the International AIDS Society-USA panel. JAMA. 1997;277:1962-9. [PMID: 9200638] CrossrefMedlineGoogle Scholar2. Yeni PG, Hammer SM, Carpenter CC, Cooper DA, Fischl MA, Gatell JM, . Antiretroviral treatment for adult HIV infection in 2002: updated recommendations of the International AIDS Society-USA Panel. JAMA. 2002;288:222-35. [PMID: 12095387] CrossrefMedlineGoogle Scholar3. Dybul M, Fauci A, Bartlett J, Kaplan J, Pau A. Guidelines for using antiretroviral agents among HIV-infected adults and adolescents. Ann Intern Med. 2002;137:381-433. LinkGoogle Scholar4. Hogg RS, Yip B, Chan KJ, Wood E, Craib KJ, O'Shaughnessy MV, . Rates of disease progression by baseline CD4 cell count and viral load after initiating triple-drug therapy. JAMA. 2001;286:2568-77. [PMID: 11722271] CrossrefMedlineGoogle Scholar5. Chen R, Westfall A, Cloud G, Chatham A, Acosta E, Raper J, et al. Long-term survival after initiation of antiretroviral therapy [Abstract]. Chicago: 8th Conference on Retroviruses and Opportunistic Infections; 2001: Abstract 341. Google Scholar6. Sterling TR, Chaisson RE, Moore RD. HIV-1 RNA, CD4 T-lymphocytes, and clinical response to highly active antiretroviral therapy. AIDS. 2001;15:2251-7. [PMID: 11698698] CrossrefMedlineGoogle Scholar7. Egger M, May M, Chne G, Phillips AN, Ledergerber B, Dabis F, . Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies. Lancet. 2002;360:119-29. [PMID: 12126821] CrossrefMedlineGoogle Scholar8. Mallon PW, Cooper DA, Carr A. HIV-associated lipodystrophy. HIV Med. 2001;2:166-73. [PMID: 11737397] CrossrefMedlineGoogle Scholar9. Miller KD, Masur H, Jones EC, Joe GO, Rick ME, Kelly GG, . High prevalence of osteonecrosis of the femoral head in HIV-infected adults. Ann Intern Med. 2002;137:17-25. [PMID: 12093241] LinkGoogle Scholar10. Palella FJ, Deloria-Knoll M, Chmiel JS, Moorman AC, Wood KC, Greenberg AE, . Survival benefit of initiating antiretroviral therapy in HIV-infected persons in different CD4+cell strata. Ann Intern Med. 2003;138:620-6. LinkGoogle Scholar11. Collins R, MacMahon S. Reliable assessment of the effects of treatment on mortality and major morbidity, I: clinical trials. Lancet. 2001;357:373-80. [PMID: 11211013] CrossrefMedlineGoogle Scholar12. Califf RM, DeMets DL. Principles from clinical trials relevant to clinical practice: Part I. Circulation. 2002;106:1015-21. [PMID: 12186809] CrossrefMedlineGoogle Scholar13. Emanuel EJ, Wendler D, Grady C. What makes clinical research ethical? JAMA. 2000;283:2701-11. [PMID: 10819955] CrossrefMedlineGoogle Scholar14. Killen J, Grady C, Folkers GK, Fauci AS. Ethics of clinical research in the developing world. Nat Rev Immunol. 2002;2:210-5. [PMID: 11913072] CrossrefMedlineGoogle Scholar Comments0 CommentsSign In to Submit A Comment Author, Article, and Disclosure InformationAffiliations: From National Institute of Allergy and Infectious Diseases; National Institutes of Health, Bethesda, MD; and University of Minnesota; Minneapolis, MN 55414.Disclosures: None disclosed.Corresponding Author: H. Clifford Lane, MD, Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, 10 Center Drive, MSC 1894, National Institutes of Health, Bethesda, MD 20892-1894; e-mail, [email protected]nih.gov.Current Author Addresses: Dr. Lane: Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, 10 Center Drive, MSC 1894, Bethesda, MD 20892-1894.Dr. Neaton: University of Minnesota, Room 220, 2221 University Avenue SE, Minneapolis, MN 55414. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoSurvival Benefit of Initiating Antiretroviral Therapy in HIV-Infected Persons in Different CD4+ Cell Strata Frank J. Palella Jr. , Maria Deloria-Knoll , Joan S. Chmiel , Anne C. Moorman , Kathleen C. Wood , Alan E. Greenberg , Scott D. Holmberg , and Metrics Cited bySerious Non-AIDS Conditions in HIV: Benefit of Early ARTLate initiation of combination antiretroviral therapy in Canada: a call for a national public health strategy to improve engagement in HIV careShould Expectations about the Rate of New Antiretroviral Drug Development Impact the Timing of HIV Treatment Initiation and Expectations about Treatment Benefits?Considerations in the rationale, design and methods of the Strategic Timing of AntiRetroviral Treatment (START) studyInitiating patients on antiretroviral therapy at CD4 cell counts above 200 cells/μl is associated with improved treatment outcomes in South AfricaHow HIV treatment could result in effective preventionUsing Mechanistic Models to Simulate Comparative Effectiveness Trials of Therapy and to Estimate Long-term Outcomes in HIV CareEarly antiretroviral therapy: the role of cohortsEffect of Early versus Deferred Antiretroviral Therapy for HIV on SurvivalTiming of initiation of antiretroviral therapy in AIDS-free HIV-1-infected patients: a collaborative analysis of 18 HIV cohort studiesShould the CD4 threshold for starting ART be raised?Lower Perceived Necessity of HAART Predicts Lower Treatment Adherence and Worse Virological Response in the ATHENA CohortFeeding of mice with Arabidopsis thaliana expressing the HIV-1 subtype C p24 antigen gives rise to systemic immune responses Improving HIV Screening and Receipt of Results by Nurse-Initiated Streamlined Counseling and Rapid TestingThe Search for Data on When to Start Treatment for HIV InfectionEarlier initiation of antiretroviral therapy in treatment-na??ve patients: implications of results of treatment interruption trialsInfluence of Alternative Thresholds for Initiating HIV Treatment on Quality-Adjusted Life Expectancy: A Decision ModelR. Scott Braithwaite, MD, MSc, Mark S. Roberts, MD, MPP, Chung Chou H. Chang, PhD, Matthew Bidwell Goetz, MD, Cynthia L. Gibert, MD, MSc, Maria C. Rodriguez-Barradas, MD, Steven Shechter, PhD, Andrew Schaefer, PhD, Kimberly Nucifora, MS, Robert Koppenhaver, MS, and Amy C. Justice, MD, PhDImpact of baseline viral load and adherence on survival of HIV-infected adults with baseline CD4 cell counts ≥ 200 cells/μlWhen to initiate antiretroviral therapy in HIV-1-infected adults: a review for clinicians and patientsImpact of Practice Changes on an Antiretroviral Budget in an HIV Care ProgramThe Case for Earlier Treatment of HIV InfectionThe Impact of Adherence on CD4 Cell Count Responses Among HIV-Infected PatientsHIV Patients in the HCUP Database: A Study of Hospital Utilization and CostsHIV Therapy — What Do We Know, and When Do We Know It?Effect of Medication Adherence on Survival of HIV-Infected Adults Who Start Highly Active Antiretroviral Therapy When the CD4+ Cell Count Is 0.200 to 0.350 × 109 cells/LEvan Wood, PhD, Robert S. Hogg, PhD, Benita Yip, BSc (Pharm), P. Richard Harrigan, PhD, Michael V. O'Shaughnessy, PhD, and Julio S.G. Montaner, MD, FRCPC 15 April 2003Volume 138, Issue 8Page: 680-681KeywordsAntiretroviral therapyHIVHIV infectionsInfectious diseasesMortalityObservational studiesPatientsRandomized trialsResearch laboratoriesViral load ePublished: 15 April 2003 Issue Published: 15 April 2003 PDF downloadLoading ...

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,051
score de la tête « metaresearch » (Gemma)0,185
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,051
Score d'incertitude au seuil0,272

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0510,185
Méta-épidémiologie (sens strict)0,0030,002
Méta-épidémiologie (sens large)0,0050,004
Bibliométrie0,0100,004
Études des sciences et des technologies0,0040,006
Communication savante0,0150,018
Science ouverte0,0060,003
Intégrité de la recherche0,0140,032
Charge utile insuffisante (le modèle a refusé de juger)0,0160,013

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,141
Tête enseignante GPT0,402
Écart entre enseignants0,262 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations38
Publié2003
Routes d'admission1
Résumé présentoui

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