Efficacy and Cost Effectiveness of Adjuvant Chemotherapy in Women with Node-Negative Breast Cancer — A Decision-Analysis Model

Abstract BACKGROUND. In 1988 the National Cancer Institute issued a Clinical Alert that has been widely interpreted as recommending that all women with node-negative breast cancer receive adjuvant chemotherapy. Acceptance of this recommendation is controversial, since many women who would not have a recurrence would be treated. METHODS. Using a decision-analysis model, we studied the cost effectiveness of chemotherapy in cohorts of 45-year-old and 60-year-old women with node-negative breast cancer by calculating life expectancy as adjusted for quality of life. The analysis evaluated different scenarios of the benefit of therapy: improved disease-free survival for five years, with a lesser effect on overall survival (base line); a lifelong benefit from chemotherapy; and a benefit in disease-free survival with no change in overall survival by year 10. The base-line analysis assumed a 30 percent reduction in the relative risk of recurrence for five years after treatment. RESULTS. For the 45-year-old woman, the base-line analysis found an average lifetime benefit from chemotherapy of 5.1 quality-months at a cost of $15,400 per quality-year. The 60-year-old women gained 4.0 quality-months at a cost of$18,800 per quality-year. Under the more and less optimistic scenarios, the benefit of chemotherapy varied from 1.4 to 14.0 quality-months for both groups. CONCLUSIONS. Chemotherapy substantially increases the quality-adjusted life expectancy of an average woman at a cost comparable to that of other widely accepted therapies. This benefit decreases markedly if the changes in long-term survival are less than in disease-free survival. Given its uncertain duration, the benefit may be too small for many women to choose chemotherapy. Selective use of chemotherapy to maximize the benefit to individual patients may be possible with refinements in risk stratification and explicit assessment of the patients\u27 risk preferences. (N Engl J Med 1991; 324:160–8.

A Quantitative Methodology for Determining the Need for Exposure-Prompted Medical Monitoring

Some toxic exposures to drugs or other environmental chemicals may create an increased risk of future disease for which periodic preventive medical screening might be desirable. However, many of these risks, even if unacceptable as a matter of public health policy, might still not be significant enough for medical monitoring (periodic diagnostic screening for latent illnesses or medical conditions) to be an appropriate medical intervention. This somewhat unintuitive, but statistically certain, conclusion can be demonstrated in relatively simple mathematical terms. Accordingly, we introduce Bayes\u27s Rule and decision analysis, a quantitative methodology commonly employed by medical practitioners. A review of current medical practices indicates that physicians decide whether to recommend monitoring for a particular exposed population by knowing the natural history of the disease and by first calculating the predictive value of a positive test ( PPV ), which will be one to five percent or greater for an endorsable monitoring exercise, absent exceptional circumstances. Rather than simply relying on the opinions of retained medical experts, this accessible quantitative method permits judges, jurists, and policymakers to more confidently and objectively decide whether medical monitoring is appropriate and necessary as a result of a specific chemical exposure

A Quantitative Methodology for Determining the Need for Exposure-Prompted Medical Monitoring

Some toxic exposures to drugs or other environmental chemicals may create an increased risk of future disease for which periodic preventive medical screening might be desirable. However, many of these risks, even if unacceptable as a matter of public health policy, might still not be significant enough for medical monitoring (periodic diagnostic screening for latent illnesses or medical conditions) to be an appropriate medical intervention. This somewhat unintuitive, but statistically certain, conclusion can be demonstrated in relatively simple mathematical terms. Accordingly, we introduce Bayes\u27s Rule and decision analysis, a quantitative methodology commonly employed by medical practitioners. A review of current medical practices indicates that physicians decide whether to recommend monitoring for a particular exposed population by knowing the natural history of the disease and by first calculating the predictive value of a positive test ( PPV ), which will be one to five percent or greater for an endorsable monitoring exercise, absent exceptional circumstances. Rather than simply relying on the opinions of retained medical experts, this accessible quantitative method permits judges, jurists, and policymakers to more confidently and objectively decide whether medical monitoring is appropriate and necessary as a result of a specific chemical exposure

EFFICACY AND COST-EFFECTIVENESS OF ADJUVANT CHEMOTHERAPY IN WOMEN WITH NODE-NEGATIVE BREAST-CANCER - A DECISION-ANALYSIS MODEL

BACKGROUND. In 1988 the National Cancer Institute issued a Clinical Alert that has been widely interpreted as recommending that all women with node-negative breast cancer receive adjuvant chemotherapy. Acceptance of this recommendation is controversial, since many women who would not have a recurrence would be treated. METHODS. Using a decision-analysis model, we studied the cost effectiveness of chemotherapy in cohorts of 45-year-old and 60-year-old women with node-negative breast cancer by calculating life expectancy as adjusted for quality of life. The analysis evaluated different scenarios of the benefit of therapy: improved disease-free survival for five years, with a lesser effect on overall survival (base line); a lifelong benefit from chemotherapy; and a benefit in disease-free survival with no change in overall survival by year 10. The base-line analysis assumed a 30 percent reduction in the relative risk of recurrence for five years after treatment. RESULTS. For the 45-year-old woman, the base-line analysis found an average lifetime benefit from chemotherapy of 5.1 quality-months at a cost of $15,400 per quality-year. The 60-year-old women gained 4.0 quality-months at a cost of$18,800 per quality-year. Under the more and less optimistic scenarios, the benefit of chemotherapy varied from 1.4 to 14.0 quality-months for both groups. CONCLUSIONS. Chemotherapy substantially increases the quality-adjusted life expectancy of an average woman at a cost comparable to that of other widely accepted therapies. This benefit decreases markedly if the changes in long-term survival are less than in disease-free survival. Given its uncertain duration, the benefit may be too small for many women to choose chemotherapy. Selective use of chemotherapy to maximize the benefit to individual patients may be possible with refinements in risk stratification and explicit assessment of the patients\u27 risk preferences. (N Engl J Med 1991; 324:160–8.

rPOP: Robust PET-Only Processing of Community Acquired Heterogeneous Amyloid-PET Data

The reference standard for amyloid-PET quantification requires structural MRI (sMRI) for preprocessing in both multi-site research studies and clinical trials. Here we describe rPOP (robust PET-Only Processing), a MATLAB-based MRI-free pipeline implementing non-linear warping and differential smoothing of amyloid-PET scans performed with any of the FDA-approved radiotracers (18F-florbetapir/FBP, 18F-florbetaben/FBB or 18F-flutemetamol/FLUTE). Each image undergoes spatial normalization based on weighted PET templates and data-driven differential smoothing, then allowing users to perform their quantification of choice. Prior to normalization, users can choose whether to automatically reset the origin of the image to the center of mass or proceed with the pipeline with the image as it is. We validate rPOP with n = 740 (514 FBP, 182 FBB, 44 FLUTE) amyloid-PET scans from the Imaging Dementia—Evidence for Amyloid Scanning – Brain Health Registry sub-study (IDEAS-BHR) and n = 1,518 scans from the Alzheimer\u27s Disease Neuroimaging Initiative (n = 1,249 FBP, n = 269 FBB), including heterogeneous acquisition and reconstruction protocols. After running rPOP, a standard quantification to extract Standardized Uptake Value ratios and the respective Centiloids conversion was performed. rPOP-based amyloid status (using an independent pathology-based threshold of ≥24.4 Centiloid units) was compared with either local visual reads (IDEAS-BHR, n = 663 with complete valid data and reads available) or with amyloid status derived from an MRI-based PET processing pipeline (ADNI, thresholds of \u3e20/\u3e18 Centiloids for FBP/FBB). Finally, within the ADNI dataset, we tested the linear associations between rPOP- and MRI-based Centiloid values. rPOP achieved accurate warping for N = 2,233/2,258 (98.9%) in the first pass. Of the N = 25 warping failures, 24 were rescued with manual reorientation and origin reset prior to warping. We observed high concordance between rPOP-based amyloid status and both visual reads (IDEAS-BHR, Cohen\u27s k = 0.72 [0.7–0.74], ∼86% concordance) or MRI-pipeline based amyloid status (ADNI, k = 0.88 [0.87–0.89], ∼94% concordance). rPOP- and MRI-pipeline based Centiloids were strongly linearly related (R2:0.95, p\u3c0.001), with this association being significantly modulated by estimated PET resolution (β= -0.016, p\u3c0.001). rPOP provides reliable MRI-free amyloid-PET warping and quantification, leveraging widely available software and only requiring an attenuation-corrected amyloid-PET image as input. The rPOP pipeline enables the comparison and merging of heterogeneous datasets and is publicly available at https://github.com/leoiacca/rPO