Decision-Making Process--Communicating Risk/Benefits: Is There an Ideal Technique?
Notice bibliographique
Résumé
During the last decade, there have been major advances in the treatment of early-stage breast cancer. The decisions a patient now must make concerning her treatment are often difficult and complex, e.g., mastectomy versus lumpectomy plus breast radiation therapy, adjuvant chemotherapy and/or hormonal therapy versus no further treatment, regional radiation therapy or no regional radiation therapy. In the past, physicians tended to make decisions for patients with little patient input. More recently, women have indicated the need for more information about their disease and a desire to be involved in decisions about their care (1). Degnar et al. (2) examined the preferences of 1012 women with breast cancer for participation in treatment decision making. Twenty-two percent of the women wanted to select their own cancer treatment (active role), 44% wanted to select their treatment collaboratively with their physician (collaborative role), and 34% wanted to delegate this responsibility to their physician (passive role). Education and age influenced the preferred role in decision making. In general, the patient/physician encounter will involve several stages, including exchange of information between the doctor and the patient, deliberation, and decision making (3). At one extreme is a paternalistic model, where information flows in one direction—from the doctor to the patient—and the doctor alone makes the decision. At the other extreme is the informed model, where again, information flows mainly in one direction, but the patient alone makes the decision. In between these models is the shared model, in which the doctor and patient share all stages of the decision-making process simultaneously. There is a two-way exchange of information, both doctor and patient reveal treatment preferences, and both agree on the decision to implement. It is the shared model for decision making that provides the foundation for the use of decision aids. Studies have demonstrated that the majority of women with breast cancer and their physicians prefer shared models for decision making (4). Studies have suggested problems with the traditional physician/patient encounter, particularly with the transfer of information and patient involvement in decision making (5,6). Siminoff et al. (5) studied 100 consecutive physician–patient encounters for adjuvant chemotherapy in women with early breast cancer to assess the consultative approach. They observed that the communication pattern, particularly that of the physician, was independent of characteristics of the patient and the severity of her disease. The risks and benefits of treatment were discussed, but the physician exchanged little in the way of specific information, and the impact of treatment on the patient's lifestyle and emotional state often was not routinely addressed. Not surprisingly, the majority of patients (60%) overestimated their chance of being cured by 20% or more and underestimated the likelihood of severe common side effects by a similar percentage. Although patients were given alternative options, physicians generally recommended one treatment, and this had a definite influence on the patient's decision. Rimer et al. (6) reviewed 116 consultations regarding adjuvant chemotherapy between physicians and patients. Clinicians, on average, told patients less than 70% of the information relevant to their disease and treatment. On the basis of these considerations, researchers and clinicians have responded by investigating better ways of transferring information to patients and supporting them in decision making. Decision aids have been defined as “interventions designed to help people make specific and deliberative choices among options by providing information on the options and outcomes relevant to the person's health status” (1). Examples of decision aids are written materials, computer-based programs, video programs, audio-guided workbooks, and decision boards. These methods differ from traditional patient education materials both in that they provide an explicit presentation of different treatment options with the associated benefits and risks and in that the information provided is often tailored to the individual characteristics of the patient and her disease. O'Connor et al. have conducted a systematic review of decision aids in various cancers (1) and other health conditions (7). The results of studies evaluating these decision aids demonstrated that they are acceptable to patients and can improve knowledge and make patients more comfortable but did not appear to have a consistent impact on patient satisfaction. There have been relatively few studies of decision aids in breast cancer. We will review the use of decision aids in women with early breast cancer who are faced with treatment options. We will not consider decision aids for early detection of breast cancer or for communicating risk for prevention. There have been five studies examining the use of decision aids in the surgical management of breast cancer (Table 1). These have all been of relatively small sample size. In the first study, Chapman et al. (8) randomly assigned 82 undergraduate psychology or nursing students to view either a videodisc or a brochure. Subjects were asked to consider a hypothetical choice of lumpectomy versus mastectomy for early breast cancer. The videodisc provided information as well as an interview with patients. Although the videodisc and brochure both increased patient knowledge, there was no difference between the interventions. Viewing the videodisc resulted in a shift in preference to lumpectomy. In a study by Street et al. (9), women who had recently had a positive biopsy for breast cancer were randomly assigned to view either a multimedia program (consisting of an interactive computer) or a brochure before the consultation with a surgeon. Knowledge and optimism questionnaires were administered at baseline assignation, after the assignation, and after the physician consultation. There were 30 patients in each group. Seventy-six percent of the computer group chose lumpectomy versus 58% who chose lumpectomy in the brochure group; this difference was not statistically significant. Both the brochure and multimedia interventions increased patient knowledge, and there was a trend in favor of the multimedia program (P = .07). No difference in optimism was detected between groups. Goel et al. (10) randomly assigned 38 surgeons in clusters to the use of an audiotape and workbook or an information brochure alone. One hundred sixty-four patients were enrolled in this study. There was no difference detected between the decision-aid and brochure groups in terms of knowledge and anxiety. There was a trend for lower decisional conflict in the decision-aid group, but the difference was not statistically significant. Whelan et al. (11) developed a decision board for use by community surgeons and their patients regarding the choice of mastectomy versus lumpectomy. The decision board consists of a visual aid and written material. A clinician administers this instrument during the patient consultation. Information is presented in an interactive step-by-step fashion. The instrument was administered to 175 women with breast cancer at the decision-making point. Ninety-eight percent of the patients reported that the board was easy to understand, and 81% indicated that it helped them to make a decision. In 90% of the consultations, surgeons found the board easy to use and helpful. In a before–after design, the rate of mastectomy increased from 12% to 27% (P<0.01). The surgical decision board is currently being evaluated in a randomized trial using a cluster randomization design. Surgeons are randomly assigned the use either of the decision aid plus usual consultation or of the usual consultation. Finally, Molenaar et al. (12) developed an interactive computer program (CD-ROM) as a decision aid. This was acceptable to 96 women with early breast cancer. Using a before–after design, there was a shift in treatment preference for breast conservation therapy. In addition, posttest levels of decision uncertainty were significantly lower after using the interactive program (P<.01). Whelan et al. (13) developed a decision board for use in women with lumpectomy who were undergoing breast irradiation. This study was initiated a number of years ago following completion of a randomized trial comparing the results of radiation therapy versus no radiation therapy in the lymph node-negative women who had undergone lumpectomy. The concept at that time was to try to identify a group at low risk for recurrence who might be spared radiation therapy. Consecutive cohorts of lymph node-negative women who had undergone lumpectomy were studied. Patients at high risk for systemic recurrence were excluded from the study. Twenty-three women underwent a consultation by the radiation oncologist alone. The next 29 women underwent consultation and, in addition, the radiation oncologist used a checklist that served as a reminder to cover a number of important information points concerning breast irradiation in the interview. Following this, 30 patients underwent the usual consultation and, in addition, were administered a decision board. The use of the decision board increased knowledge compared with the consultation alone and with the consultation plus checklist. The instrument also appeared to facilitate shared decision making and empower women in the decision-making process. Ninety-seven percent of patients in the board group felt that they were offered a choice concerning breast irradiation compared with 70% in the consultation group (P = .02). Eighty percent of patients in the board group reported making a decision without a formal recommendation from their physician, compared with only 8% in the consultation group (P<.01). Levine et al. (14) developed a decision board for use in women with high-risk lymph node-negative breast cancer who were considering adjuvant chemotherapy. The validity and reliability of the board were established in healthy volunteers. The instrument was found to be acceptable and helpful in 37 newly presenting women with high-risk lymph node-negative breast cancer who were considering adjuvant chemotherapy. This type of board has been evaluated in a randomized trial. One hundred seventy-six women with lymph node-negative breast cancer were randomly assigned to either the medical oncology consultation or the medical oncology consultation plus the decision board. The outcome measures include knowledge, satisfaction, and treatment choice. Ravdin et al. (15) have developed a decision aid in the form of a simple-to-use computer program. This program is designed to produce prognostic estimates of outcome both with and without therapy based on estimates of individual patient prognosis and estimates of the efficacy of different adjuvant therapy options. The computer program can present this information on the screen for the physician and as printed pages for use with patients. This decision aid has been evaluated in a clinical trial in which 44 doctors were randomly assigned to the usual consultation approach versus the consultation plus decision aid. Four hundred four patients participated in this trial. The endpoints include knowledge, satisfaction, and treatment choice. In general, decision aids have been shown to improve patient knowledge and make patients more comfortable with treatment decision making. There have been relatively few studies of decision aids in patients with early-stage breast cancer. Nonetheless, it appears that women with early breast cancer find decision aids helpful in decision making and that decision aids can improve these women's knowledge concerning treatment options. Decision aids facilitate shared decision making in women with breast cancer. Physicians and surgeons can use decision aids in their practice and may find them helpful. Future research is required to determine whether decision aids can improve such outcomes as patient satisfaction, quality of life in the long term, and unexplained practice variation. In addition, research will determine whether particular decision aids are better than others or whether a particular aid is better for a particular patient group or intervention. Mastectomy versus lumpectomy Mastectomy versus lumpectomy
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,017 | 0,029 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,004 |
| Communication savante | 0,005 | 0,006 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,004 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».