BACKGROUND: A significant improvement in overall survival (OS) was demonstrated in patients with advanced hepatocellular carcinoma (HCC) who received sorafenib (Sor) in the Sorafenib HCC Assessment Randomized Protocol (SHARP) study, in contrast to a response rate (RR) of 2% assessed according to Response Evaluation Criteria in Solid Tumors (RECIST). Modified RECIST (mRECIST) were developed to assess the response in patients with HCC, based on measurement of viable tumor with arterial enhancement on a computed tomography (CT) scan. In the current study, mRECIST were evaluated and were compared with RECIST in patients who received Sor for advanced HCC. METHODS: The authors retrospectively analyzed 53 patients who received Sor for advanced HCC. Patients must to have undergone a 4‐phase CT scan before treatment and repeatedly thereafter. CT scans were analyzed using RECIST 1.1 and mRECIST. RESULTS: The rates of objective response (OR), stable disease (SD), and progressive disease (PD) were 2%, 79%, and 19%, respectively, according to RECIST and 23%, 57%, and 21%, respectively, according to mRECIST (P < .001). Patients who achieved an OR according to mRECIST had a longer OS than nonresponding patients with SD or PD (median OS, 18 months and 8 months, respectively; P = .013). In the 42 patients who achieved SD according to RECIST, OS differed depending on tumor response according to mRECIST, with a median OS of 17 months, 10 months, and 4 months for patients who achieved an OR (n = 11), SD (n = 29), and PD (n = 2), respectively (P = .016). CONCLUSIONS: The current series validated mRECIST in patients who received Sor for advanced HCC. The majority of patients who had SD according to RECIST had a different prognosis according to mRECIST. The results indicated that, for patients with HCC, mRECIST should be used for the standard assessment of treatment efficacy, particularly in patients who are receiving antiangiogenic drugs. Cancer 2012;. © 2011 American Cancer Society.

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Airborne light detection and ranging (LiDAR) bathymetry appears to be a useful technology for bed topography mapping of non-navigable areas, offering high data density and a high acquisition rate. However, few studies have focused on continental waters, in particular, on very shallow waters (<2 m) where it is diffi cult to extract the surface and bottom positions that are typically mixed in the green LiDAR signal. This paper proposes two new processing methods for depth extraction based on the use of different LiDAR signals [green, near-infrared (NIR), Raman] of the SHOALS-1000T sensor. They have been tested on a very shallow coastal area (Golfe du Morbihan, France) as an analogy to very shallow rivers. The fi rst method is based on a combination of mathematical and heuristic methods using the green and the NIR LiDAR signals to cross validate the information delivered by each signal. The second method extracts water depths from the Raman signal using statistical methods such as principal components analysis (PCA) and classifi cation and regression tree (CART) analysis. The obtained results are then compared to the reference depths, and the performances of the different methods, as well as their advantages/disadvantages are evaluated. The green/NIR method supplies 42% more points compared to the operator process, with an equivalent mean error (−4·2 cm verusu −4·5 cm) and a smaller standard deviation (25·3 cm verusu 33·5 cm). The Raman processing method provides very scattered results (standard deviation of 40·3 cm) with the lowest mean error (−3·1 cm) and 40% more points. The minimum detectable depth is also improved by the two presented methods, being around 1 m for the green/NIR approach and 0·5 m for the statistical approach, compared to 1·5 m for the data processed by the operator. Despite its ability to measure other parameters like water temperature, the Raman method needed a large amount of reference data to provide reliable depth measurements, as opposed to the green/NIR method.

Purpose This paper aims to explore the nexus between integrated reporting and sustainability embeddedness. It seeks to contribute to a better understanding of the nexus by obtaining in-depth insight from the sensemaking of those in practice. Design/methodology/approach A single exploratory case study design strategy was applied to a leading stock exchange listed company in the property industry in South Africa. Rich qualitative data were gathered by applying multiple data gathering techniques to a diverse group of employees within the case company. Findings This empirical study contributes a metaphor of a cog and chain and nine themes that elucidate employee sensemaking at the nexus. Integrated reporting was found to drive sustainability embeddedness and foster changes within the organisation. The themes offer in-depth insight into how employees made sense of integrated reporting as a driver for sustainability embeddedness. Research limitations/implications The findings emerged from a single case study that operated in a mandatory disclosure context and are therefore not generalisable. The findings reflect the intended outcomes of integrated reporting and further research to explore the unintended outcomes and challenges associated with integrated reporting is suggested. Practical implications The study contributes to a growing practice based agenda by offering a better understanding of how integrated reporting and sustainability are conceptualised and adopted in practice. Social implications The findings offer organisations’ guidance on integrated reporting and sustainability embeddedness adoption which can have vast implications for society and the environment. Originality/value The study responds to gaps in the literature and calls for studies to explore the intersection between integrated reporting and sustainability embeddedness by engaging those in practice.