Using biomarkers to allocate patients in a response-adaptive clinical trial.

In this paper, we discuss a response adaptive randomization method, and why it should be used in clinical trials for rare diseases compared to a randomized controlled trial with equal fixed randomization. The developed method uses a patient's biomarkers to alter the allocation probability to each treatment, in order to emphasize the benefit to the trial population. The method starts with an initial burn-in period of a small number of patients, who with equal probability, are allocated to each treatment. We then use a regression method to predict the best outcome of the next patient, using their biomarkers and the information from the previous patients. This estimated best treatment is assigned to the next patient with high probability. A completed clinical trial for the effect of catumaxomab on the survival of cancer patients is used as an example to demonstrate the use of the method and the differences to a controlled trial with equal allocation. Different regression procedures are investigated and compared to a randomized controlled trial, using efficacy and ethical measures.

Predicting cancer evolution for patient benefit: Renal cell carcinoma paradigm.

Evolutionary features of cancer have important clinical implications, but their evaluation in the clinic is currently limited. Here, we review current approaches to reconstruct tumour subclonal structure and discuss tumour sampling method and experimental design influence. We describe clear-cell renal cell carcinoma (ccRCC) as an exemplar for understanding and predicting cancer evolutionary dynamics. Finally, we discuss how understanding cancer evolution can benefit patients.

Augmented Features Synergize Radiomics in Post-Operative Survival Prediction and Adjuvant Therapy Recommendation for Non-Small Cell Lung Cancer.

BACKGROUND: Owing to the cytotoxic effect, it is challenging for clinicians to decide whether post-operative adjuvant therapy is appropriate for a non-small cell lung cancer (NSCLC) patient. Radiomics has proven its promising ability in predicting survival but research on its actionable model, particularly for supporting the decision of adjuvant therapy, is limited. METHODS: Pre-operative contrast-enhanced CT images of 123 NSCLC cases were collected, including 76, 13, 16, and 18 cases from R01 and AMC cohorts of The Cancer Imaging Archive (TCIA), Jiangxi Cancer Hospital and Guangdong Provincial People's Hospital respectively. From each tumor region, 851 radiomic features were extracted and two augmented features were derived therewith to estimate the likelihood of adjuvant therapy. Both Cox regression and machine learning models with the selected main and interaction effects of 853 features were trained using 76 cases from R01 cohort, and their test performances on survival prediction were compared using 47 cases from the AMC cohort and two hospitals. For those cases where adjuvant therapy was unnecessary, recommendations on adjuvant therapy were made again by the outperforming model and compared with those by IBM Watson for Oncology (WFO). RESULTS: The Cox model outperformed the machine learning model in predicting survival on the test set (C-Index: 0.765 vs. 0.675). The Cox model consists of 5 predictors, interestingly 4 of which are interactions with augmented features facilitating the modulation of adjuvant therapy option. While WFO recommended no adjuvant therapy for only 13.6% of cases that received unnecessary adjuvant therapy, the same recommendations by the identified Cox model were extended to 54.5% of cases (McNemar's test p = 0.0003). CONCLUSIONS: A Cox model with radiomic and augmented features could predict survival accurately and support the decision of adjuvant therapy for bettering the benefit of NSCLC patients.

[Statement: Requirements for the assessment of surgical innovations]. / Statement: Anforderungen an Methoden zur Bewertung chirurgischer Innovationen.

The term "innovation" refers to new products, but also to the process of developing and distributing new products and procedures. The operative disciplines are often associated with innovations because of their continuous, stepwise adaptation of daily practice to established procedures. Medical devices play a significant role in integrating surgical technology with surgical experience. The success of a surgical innovation and other invasive treatments does not only depend on the surgical procedure, but also on the context of the whole treatment process including the pre- and postoperative phase, the interaction of the surgical team and the setting. High standards have been set for the assessment of surgical innovations in terms of patient safety, efficacy and patient benefit, which will be discussed in the present paper. A stepwise approach to evaluation will be used, split into preclinical development, clinical development (feasibility and safety), evaluation phase (efficacy and patient benefit) and longtime surveillance. Our paper is based on the expert-based consented IDEAL approach as well as the consented recommendations of the European Association of Endoscopic Surgery (EAES). (As supplied by publisher).

Fractional carbon dioxide laser resurfacing of rhytides and photoaged skin--a prospective clinical study on patient expectation and satisfaction.

BACKGROUND: Fractional CO2 -laser resurfacing is increasingly used for treating rhytides and photoaged skin because of its favorable benefit-risk ratio. A key outcome measure and treatment goal in aesthetic laser therapy is patient satisfaction. However, few data are available on patient-reported outcomes after fractional ablative skin-resurfacing. OBJECTIVES: To compare patient expectations before and patient satisfaction after three fractional CO2 -laser treatments and to correlate objectively measured wrinkle reduction with patient satisfaction after treatment. METHODS: We investigated patient expectation and satisfaction using a 14-item questionnaire in 24 female patients. We assessed the skin-related quality of life and patient satisfaction with skin appearance. We profilometrically measured wrinkle size in four facial areas before and three months after treatment and investigated correlations between wrinkle reduction and patient satisfaction. RESULTS: The high patient expectations before treatment (ceiling effect) were actually slightly exceeded. The average score of 14 items delineating patient satisfaction with laser treatment was higher (4.64 ± 0.82; n = 24) than the respective expectations before treatment (4.43 ± 0.88; n = 24). Skin-related quality of life and patient satisfaction with skin appearance had significantly improved after the last treatment. Patients dissatisfied with their skin appearance before treatment (mean 2.1 ± 1.5; evaluated on a scale ranging from 0-6) were satisfied (mean 5.1 ± 1.2) (P < 0.001) with skin appearance at the follow-up. Patient satisfaction with skin appearance was not correlated to the profilometrically measured reduction of wrinkle size of any facial area. CONCLUSIONS: Our results show high patient satisfaction with ablative fractional skin resurfacing, also regarding improved self-esteem and self-satisfaction despite high pre-treatment expectations. Skin-specific quality of life had significantly improved. Thus, this treatment modality can be recommended for patients with photoaged skin wishing to improve skin appearance.

Evaluation of patient-relevant outcomes of lymphedema and lipedema treatment: development and validation of a new benefit tool.

OBJECTIVES: Patient-relevant treatment benefit is traditionally measured with health-related quality of life (HRQoL) instruments. The Patient Benefit Index (PBI) methodology allows for a more direct measurement, with the patients rating both importance and achievement of treatment goals. Here, we developed and validated a PBI version specific for the assessment of benefit in lymphedema and lipedema treatment (PBI-L). METHODS: The development included five steps: (1) open item collection; (2) consensus of items in a multidisciplinary expert panel; (3) application of the German PBI-L in a cross-sectional study (n = 301); (4) translation into English; (5) application of the English PBI-L in a randomized clinical trial (n = 82). Subscales were developed using factor analysis. Construct validity was analyzed by correlating PBI-L and convergent criteria such as HRQoL and quality of care. To test for responsiveness, the association to change in HRQoL measures was computed. RESULTS: Floor and ceiling effects were low. There were few missing values. Two well-interpretable subscales were found with Cronbach's alpha >0.8 each. Global and subscale scores correlated with convergent criteria and with change in disease-specific HRQoL, but not with change in generic HRQoL. CONCLUSIONS: The PBI-L is an internally consistent, valid, and responsive instrument for the assessment of patient-relevant benefit of edema treatment.