Clinical trial: Efficacy of a low or modified fat diet for the prevention of gastrointestinal toxicity in patients receiving radiotherapy treatment for pelvic malignancies.

BACKGROUND: Inflammatory responses to pelvic radiotherapy can result in severe changes to normal gastrointestinal function with potentially severe long-term effects. Reduced or modified fat diets may confer benefit. METHODS: This randomised controlled trial recruited patients with gynaecological, urological or lower gastrointestinal malignancy due to receive radical radiotherapy. Patients were randomised to a low fat (20% total energy from long chain triglycerides), modified fat (20% from long chain triglycerides and 20% from medium chain triglycerides) or normal fat diet (40% total energy from long chain triglycerides). The primary outcome was a difference in change in Inflammatory Bowel Disease Questionnaire--Bowel (IBDQ-B) score, from the start to end of radiotherapy. RESULTS: A total of 117 patients with pelvic tumours (48% urological; 32% gastrointestinal; 20% gynaecological), with mean (SD) age: 65 (11.0) years, male:female ratio: 79:38, were randomised. The mean (SE) fall in paired IBDQ-B score was -7.3 (0.9) points, indicating a worsening toxicity. Differences between groups were not significant: P = 0.914 (low versus modified fat), P = 0.793 (low versus normal fat) and P = 0.890 (modified versus normal fat). The difference in fat intake between low and normal fat groups was 29.5 g [1109 kJ (265 kcal)] amounting to 11% (of total energy intake) compared to the planned 20% differential. Full compliance with fat prescription was only 9% in the normal fat group compared to 93% in the low fat group. CONCLUSIONS: A low or modified fat diet during pelvic radiotherapy did not improve gastrointestinal symptom scores compared to a normal fat intake. An inadequate differential in fat intake between the groups may have confounded the results.

Phylogenetic super-networks from partial trees.

In practice, one is often faced with incomplete phylogenetic data, such as a collection of partial trees or partial splits. This paper poses the problem of inferring a phylogenetic super-network from such data and provides an efficient algorithm for doing so, called the Z-closure method. Additionally, the questions of assigning lengths to the edges of the network and how to restrict the "dimensionality" of the network are addressed. Applications to a set of five published partial gene trees relating different fungal species and to six published partial gene trees relating different grasses illustrate the usefulness of the method and an experimental study confirms its potential. The method is implemented as a plug-in for the program SplitsTree4.