Measures of treatment benefit

In general it can be shown that the approach following the signal-to-noise ratio method is mathematically very similar to the standard formulation of the chi-square test using observed and expected frequencies, and in practice they will invariably give very similar results. Altman (1991) (Section 10.7.4) provides more detail on this connection. 

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Measures of treatment benefit for categorical and ordinal data... 

In projecting results of short-term trials over patients lifetimes, it is typical to present at least two of the many potential projections of lifetime treatment benefit. A one-time effect model assumes that the clinical benefit observed in the trial is the only clinical benefit received by patients. Under this model, after the trial has ended, the conditional probability of disease progression for patients is the same in both arms of the trial. Given that it is unlikely that a therapy will lose all benefits as soon as one stops measuring them, this projection method generally is pessimistic compared to the actual outcome. A continuous-benefit effect model assumes that the clinical benefit observed in the trial is continued throughout the patients lifetimes. Under this model, the conditional probability of disease progression for treatment and control patients continues at the same rate as that measured in the clinical trial. In contrast to the one-time model, this projection of treatment benefit most likely is optimistic compared to the treatment outcome. 

The primary endpoint should not be confused with a summary measure of the benefit. For example, the primary endpoint may be a binary endpoint, survival beyond two years/death within two years, while the primary evaluation is based upon a comparison of two year survival rates between two treatments. The primary endpoint is not the proportion surviving two years, it is binary outcome survival beyond two years/death within two years, the variable measured at the patient level. 

Everyone is familiar with the measurement of the benefit of treatment in saving or extending life, i.e. life expectancy the measure is the quantity of life (in years). But it is evident that life may be extended and yet have a low quality, even to the point that it is not worth having at all. It is therefore useful to have a unit of health measurement that combines the quality of life with its quality to allow individual and sodal decisions to be made on a sounder basis than mere intuition. To meet this need economists have developed the quality-adjusted-life-year (QALY) estimations of years of life expectancy are modified according to estimations of quality of life. 

Knapp MR) (1998). Measuring the economic benefit of treatment with atypical antipsychotics. Eur Psychiatry (suppl. 1), 37-4 5s. 

Nonpharmacologic Therapy Pruritus associated with CKD is difficult to alleviate. It is important to evaluate other potential dermatologic causes of pruritus to maximize the potential for relief. Adequate dialysis is generally the first line of treatment in patients with pruritus. However, this has not been shown to decrease the incidence of pruritus significantly. Maintaining proper nutritional intake, especially with regard to dietary phosphorus and protein intake, may lessen the degree or occurrence of pruritus. Patients who do not attain relief from other measures may benefit from ultraviolet B phototherapy. 

Although increases in bone mineral density have been reported at other sites, most of the clinically significant fractures occur in the hip or spine, and these sites have become clinically important measures in the trials. These increases in bone mineral density are an important marker of treatment effects and are related to the benefits found in larger trials of decreased fracture risk. 

One potential difficulty of cost-benefit analysis is that it requires researchers to express an intervention s costs and outcomes in the same units. Thus, monetary values must be associated with years of life lost and morbidity due to disease and with years of life gained and morbidity avoided due to intervention. Expressing costs in this way is obviously difficult in health care analyses. Outcomes (treatment benefits) may be difficult to measure in units of currency. Translating disease and treatment outcomes into monetary measures may be more difficult than translating them into clinical outcome measures, such as years of life saved or years of life saved adjusted for quality. 

The importance of this effort is illustrated in the following hypothetical example. A new therapy is under development that reduces the absolute risk of dying from a chronic disease by 50% as measured in a one-year trial. However, this therapy is not curative. A four-year trial was initiated at the same time as the one-year trial. The first-year results were the same in both the four-year trial and the one-year trial. However, there was an increased risk of death for treatment patients in the second and third year of the four-year trial, and by the end of the third year of the trial the survival rate was identical in the treatment and control arms of the four-year trial. While there was a clear benefit to the new therapy in terms of postponing events from the first year of treatment to later years, the economic assessment of the therapy would suggest a greatly reduced treatment benefit from the four-year trial as compared with the one-year trial. 

Benefits of treatment were also seen on measures of activities of daily living and behavioural disturbances. Although there is less evidence for other than mild to moderate dementia. There is evidence of more adverse events in total in the patients treated with a ChEl than with placebo. Although many types of adverse event were reported, nausea, vomiting, diarrhoea, were significantly more frequent. 

This choice should allow, amongst other things, a clear quantitative measure of benefit at the individual patient level. As we will see, identifying new treatments is not just about statistical significance, it is also about clinical importance and the... 

There may also be circumstances where a categorisation combines responses measured, on different domains of action for example to give a single dichotomous responder/non-responder outcome. There are connections here with global assessment variables. This approach is taken in Alzheimer s disease where the effect of treatment is ultimately expressed in terms of the proportion of patients who achieve a meaningful benefit (response) see the CPMP (1997) Note for Guidance on Medicinal Products in the Treatment of Alzheimer s Disease . In oncology. 

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