Quality of life after postmastectomy radiotherapy in patients with intermediate-risk breast cancer (SUPREMO): 2-year follow-up results of a randomised controlled trial

Background Postmastectomy radiotherapy in patients with four or more positive axillary nodes reduces breast cancer mortality, but its role in patients with one to three involved nodes is controversial. We assessed the effects of postmastectomy radiotherapy on quality of life (QOL) in women with intermediate-risk breast cancer. Methods SUPREMO is an open-label, international, parallel-group, randomised, controlled trial. Women aged 18 years or older with intermediate-risk breast cancer (defined as pT1–2N1; pT3N0; or pT2N0 if also grade III or with lymphovascular invasion) who had undergone mastectomy and, if node positive, axillary surgery, were randomly assigned (1:1) to receive chest wall radiotherapy (50 Gy in 25 fractions or a radiobiologically equivalent dose of 45 Gy in 20 fractions or 40 Gy in 15 fractions) or no radiotherapy. Randomisation was done with permuted blocks of varying block length, and stratified by centre, without masking of patients or investigators. The primary endpoint is 10-year overall survival. Here, we present 2-year results of QOL (a prespecified secondary endpoint). The QOL substudy, open to all UK patients, consists of questionnaires (European Organisation for Research and Treatment of Cancer QLQ-C30 and QLQ-BR23, Body Image Scale, Hospital Anxiety and Depression Scale [HADS], and EQ-5D-3L) completed before randomisation, and at 1, 2, 5, and 10 years. The prespecified primary outcomes within this QOL substudy were global QOL, fatigue, physical function, chest wall symptoms, shoulder and arm symptoms, body image, and anxiety and depression. Data were analysed by intention to treat, using repeated mixed-effects methods. This trial is registered with the ISRCTN registry, number ISRCTN61145589. Findings Between Aug 4, 2006, and April 29, 2013, 1688 patients were enrolled internationally and randomly assigned to receive chest wall radiotherapy (n=853) or not (n=835). 989 (79%) of 1258 patients from 111 UK centres consented to participate in the QOL substudy (487 in the radiotherapy group and 502 in the no radiotherapy group), of whom 947 (96%) returned the baseline questionnaires and were included in the analysis (radiotherapy, n=471; no radiotherapy, n=476). At up to 2 years, chest wall symptoms were worse in the radiotherapy group than in the no radiotherapy group (mean score 14·1 [SD 15·8] in the radiotherapy group vs 11·6 [14·6] in the no radiotherapy group; effect estimate 2·17, 95% CI 0·40–3·94; p=0·016); however, there was an improvement in both groups between years 1 and 2 (visit effect −1·34, 95% CI −2·36 to −0·31; p=0·010). No differences were seen between treatment groups in arm and shoulder symptoms, body image, fatigue, overall QOL, physical function, or anxiety or depression scores. Interpretation Postmastectomy radiotherapy led to more local (chest wall) symptoms up to 2 years postrandomisation compared with no radiotherapy, but the difference between groups was small. These data will inform shared decision making while we await survival (trial primary endpoint) results. Funding Medical Research Council, European Organisation for Research and Treatment of Cancer, Cancer Australia, Dutch Cancer Society, Trustees of Hong Kong and Shanghai Banking Corporation

Functional architecture of the foveola revealed in the living primate.

The primate foveola, with its high cone density and magnified cortical representation, is exquisitely specialized for high-resolution spatial vision. However, uncovering the wiring of retinal circuitry responsible for this performance has been challenging due to the difficulty in recording receptive fields of foveal retinal ganglion cells (RGCs) in vivo. In this study, we use adaptive optics scanning laser ophthalmoscopy (AOSLO) to image the calcium responses of RGCs in the living primate, with a stable, high precision visual stimulus that allowed us to localize the receptive fields of hundreds of foveal ganglion cells. This approach revealed a precisely radial organization of foveal RGCs, despite the many distortions possible during the extended developmental migration of foveal cells. By back projecting the line connecting RGC somas to their receptive fields, we have been able to define the 'physiological center' of the foveola, locating the vertical meridian separating left and right hemifields in vivo

Perceiving polarization with the naked eye: characterization of human polarization sensitivity

Like many animals, humans are sensitive to the polarization of light. We can detect the angle of polarization using an entoptic phenomenon called Haidinger's brushes, which is mediated by dichroic carotenoids in the macula lutea. While previous studies have characterized the spectral sensitivity of Haidinger's brushes, other aspects remain unexplored. We developed a novel methodology for presenting gratings in polarization-only contrast at varying degrees of polarization in order to measure the lower limits of human polarized light detection. Participants were, on average, able to perform the task down to a threshold of 56%, with some able to go as low as 23%. This makes humans the most sensitive vertebrate tested to date. Additionally, we quantified a nonlinear relationship between presented and perceived polarization angle when an observer is presented with a rotatable polarized light field. This result confirms a previous theoretical prediction of how uniaxial corneal birefringence impacts the perception of Haidinger's brushes. The rotational dynamics of Haidinger's brushes were then used to calculate corneal retardance. We suggest that psychophysical experiments, based upon the perception of polarized light, are amenable to the production of affordable technologies for self-assessment and longitudinal monitoring of visual dysfunctions such as age-related macular degeneration

Spatial response of RGCs from M3 in the large FOV condition.

Some example responses of L-M/M-L chromatic opponent RGCs from M3 at the large FOV, where each plot is the response of a different cell to drifting gratings (6 Hz) of spatial frequencies from 2–34 c/deg. These cells were chosen to showcase different cell responses and are not necessarily special or representative of the population. Purple and Orange curves show two separate experiments that were averaged together (Gray curve). The Blue curves are simple difference of Gaussians fits (not the full ISETBio modeling, for reasons explained below) to each average. Each plot title includes the cell’s unique label “cN”, and five parameters—the center strength Kc, the center radius rc, the surround strength Ks, the surround radius rs, and a goodness of fit value for the difference of Gaussians. As can be easily seen, many of the cells do not exhibit high spatial frequency falloff at the range of spatial frequencies measured, and so the difference of Gaussians either fits poorly or produces fit parameters that are highly irregular or suspect such as center sizes much smaller than the size of a single cone. For this reason, these data were not incorporated into the modelling in the main body, as higher spatial frequency responses were needed to properly fit many of these cell responses. There were 48 such L-M/M-L chromatic opponent cells in the large FOV in M3 out of 145 measured cells. In M2, there was only one experiment measuring response to spatial frequency and it suffered from the same lack of high spatial frequency measurements as the data shown here. Full data from both animals can be shared upon request. (PDF)</p

Effect of physiological optics on RGC STFs.

a. Gray disks depict STF data measured using the AOSLO for three RGCs, and the black lines show the STFs from the ISETBio model fit to these cells. The cone weights from the model fits are used to predict the STF that would be measured under the animal’s own physiological optics (as characterized by wavefront-aberration measurements taken during the experiment) with a 2.5 mm pupil. These model-predicted STFs are depicted by the red disks. A simple DoG model is then fitted to the predicted STF data (red line) for comparison to measurements obtained in traditional in vivo neurophysiological experiments (e.g. Croner & Kaplan [9]). b. Demonstration of the effect of physiological optics on the STF. The left panel depicts the STFs of the RF center and the RF surround of a model RGC as they would be measured using diffraction-limited optics (pink and blue, respectively), whereas the composite STF is depicted by the gray disks. The middle panels depict the MTFs of three hypothetical physiological optical systems with progressively larger Gaussian point spread functions. The corresponding STFs that would be measured under these physiological optical systems are depicted in the right panels. Note the difference in scale between left y-axis (for the center and surround STFs) and right y-axis (for composite STFs).</p

ISETBio model receptive field estimates for four additional RGCs.

Each row shows the model fits to a different cell’s STF using the single cone center/0.067D residual defocus model.</p

Optimization of residual defocus for different RGCs.

For each cell the optimal residual defocus value for the single cone center and multi-cone center model scenarios was calculated to gauge variability from the chosen 0.067 D reported in the main text. For each cell, the RMSE is shown for various residual defocus values for both model scarios. Cells are labeled L1-11 or M1-4 according to whether we believed they were likely to contain an L cone or M cone at their center. (PDF)</p