Differentiating poor validity from probable impairment on the medical symptom validity test: a cross-validation study

Aims: In neuropsychological evaluations, it is often difficult to ascertain whether poor performance on measures of validity is due to poor effort or malingering, or whether there is genuine cognitive impairment. Dunham and Denney created an algorithm to assess this question using the Medical Symptom Validity Test (MSVT). We assessed the ability of their algorithm to detect poor validity versus probable impairment, and concordance of failure on the MSVT with other freestanding tests of performance validity.

Methods: Two previously published datasets (n?=?153 and n?=?641, respectively) from outpatient neuropsychological evaluations were used to test Dunham and Denney’s algorithm, and to assess concordance of failure rates with the Test of Memory Malingering and the forced choice measure of the California Verbal Learning Test, two commonly used performance validity tests.

Results: In both datasets, none of the four cutoff scores for failure on the MSVT (70%, 75%, 80%, or 85%) identified a poor validity group with proportionally aligned failure rates on other freestanding measures of performance validity. Additionally, the protocols with probable impairment did not differ from those with poor validity on cognitive measures.

Conclusions: Despite what appeared to be a promising approach to evaluating failure on the easy MSVT subtests when clinical data are unavailable (as recommended in the advanced interpretation program, or advanced interpretation [AI], of the MSVT), the current findings indicate the AI remains the gold standard for doing so. Future research should build on this effort to address shortcomings in measures of effort in neuropsychological evaluations.     

Cured Today,Ill Tomorrow: A Method for Including Future Unrelated Medical Costs in Economic Evaluation in England and Wales

ObjectivesIn many countries, future unrelated medical costs occurring during life-years gained are excluded from economic evaluation, and benefits of unrelated medical care are implicitly included, leading to life-extending interventions being disproportionately favored over quality of life-improving interventions. This article provides a standardized framework for the inclusion of future unrelated medical costs and demonstrates how this framework can be applied in England and Wales.MethodsData sources are combined to construct estimates of per-capita National Health Service spending by age, sex, and time to death, and a framework is developed for adjusting these estimates for costs of related diseases. Using survival curves from 3 empirical examples illustrates how our estimates for unrelated National Health Service spending can be used to include unrelated medical costs in cost-effectiveness analysis and the impact depending on age, life-years gained, and baseline costs of the target group.ResultsOur results show that including future unrelated medical costs is feasible and standardizable. Empirical examples show that this inclusion leads to an increase in the ICER of between 7% and 13%.ConclusionsThis article contributes to the methodology debate over unrelated costs and how to systematically include them in economic evaluation. Results show that it is both important and possible to include future unrelated medical costs.     

薄层色谱法在当前中药质量标准中的应用探讨

薄层色谱鉴别在历版《中国药典》中的应用经历了从无到有、从少到多的过程；而薄层扫描含量测定在最近几版《中国药典》中的应用比例逐渐降低。随着对中药质量标准体系要求的进一步提高，薄层色谱法的不足之处陆续显现，如仪器普及率低、设备并不简单、结果重复性和稳定性较差、鉴别速度及准确性不及高效液相色谱法、展开剂毒性大等，逐渐不合时宜。在制定中药质量标准时，研究者不应该墨守成规，薄层色谱鉴别也不应该是雷打不动的定性鉴别必备选项。高效液相色谱法具备完全取代薄层色谱法的可行性，薄层色谱法可作为高效液相色谱法的补充。为充分降低检测成本、缩短检测周期、提高鉴别效率，笔者建议中药质量标准体系应该大幅减少薄层色谱鉴别方法的应用，增加高效液相特征图谱鉴定，尽量做到“一个条件，一张图谱”；除非确有必要，《中国药典》等国家质量标准体系应将薄层色谱鉴别作为推荐方法，而非强制标准。     

Challenges with Forecasting Budget Impact: A Case Study of Six ICER Reports

Background

Payers frequently rely on budget impact model (BIM) results to help determine drug coverage policy and its effect on their bottom line. It is unclear whether BIMs typically overestimate or underestimate real-world budget impact.

Care of Seniors with Breast Cancer – Treatment Received and Refining Decision Making

AimsTreatment decisions for older patients with breast cancer are complex and evidence is largely extrapolated from younger populations. Frailty and comorbidity need to be considered. We studied the baseline characteristics and treatment decisions in older patients in Christchurch with breast cancer and assessed survival outcomes and prognostic/discriminatory performance of several tools.Materials and methodsWe searched the Canterbury Breast Cancer Registry and identified patients aged 70 years or older at diagnosis with invasive, non-metastatic breast cancer between 1 June 2009 and 30 June 2015. We retrieved demographics, treatment and outcome information. Overall survival and breast cancer-specific survival were estimated. Tools analysing performance status and comorbidity were assessed for their prognostic and discriminatory power.ResultsIn total, 440 patients were identified. Primary surgery was carried out for 362 patients (82.3%): breast-conserving surgery in 114 (of whom 88.6% received radiation therapy); mastectomy in 248 (of whom 24.6% received radiation). Hormone therapy was given for 265 (71.1%) patients with oestrogen receptor-positive cancers. Two hundred and seventy-four (62.3%) patients received full standard treatment, which was associated with significantly improved 5-year survival and 5-year breast cancer-specific survival. The median estimated overall survival was 8.2 years (95% confidence interval 7.3–9.1 years). Of those who died, 71.3% of deaths were due to causes other than breast cancer or unknown causes. The comorbidity-adjusted life expectancy (CALE) showed partial prognostic accuracy. CALE, Charlson and Eastern Cooperative Oncology Group tools all showed discriminatory value.ConclusionIn this population-based series of older patients with breast cancer, showing high levels of primary and adjuvant treatment, patients were more likely to die of causes other than breast cancer. Performance status and comorbidity tools showed prognostic and discriminatory potential in this population supporting their use in treatment decision making. CALE showed the most potential to improve treatment decisions but requires validation in this population to improve prognostic accuracy.