6 research outputs found
Late radiation-induced bowel syndromes, tobacco smoking, age at treatment and time since treatment – gynecological cancer survivors
<p><b>Background:</b> It is unknown whether smoking; age at time of radiotherapy or time since radiotherapy influence the intensity of late radiation-induced bowel syndromes.</p> <p><b>Material and methods:</b> We have previously identified 28 symptoms decreasing bowel health among 623 gynecological-cancer survivors (three to twelve years after radiotherapy) and 344 matched population-based controls. The 28 symptoms were grouped into five separate late bowel syndromes through factor analysis. Here, we related possible predictors of bowel health to syndrome intensity, by combining factor analysis weights and symptom frequency on a person-incidence scale.</p> <p><b>Results:</b> A strong (<i>p</i> < .001) association between smoking and radiation-induced urgency syndrome was found with a syndrome intensity (normalized factor score) of 0.4 (never smoker), 1.2 (former smoker) and 2.5 (current smoker). Excessive gas discharge was also related to smoking (<i>p</i> = .001). Younger age at treatment resulted in a higher intensity, except for the leakage syndrome. For the urgency syndrome, intensity decreased with time since treatment.</p> <p><b>Conclusions:</b> Smoking aggravates the radiation-induced urgency syndrome and excessive gas discharge syndrome. Smoking cessation may promote bowel health among gynecological-cancer survivors. Furthermore, by understanding the mechanism for the decline in urgency-syndrome intensity over time, we may identify new strategies for prevention and alleviation.</p
Dose-response relationships of the sigmoid for urgency syndrome after gynecological radiotherapy
<p><b>Purpose:</b> To find out what organs and doses are most relevant for ‘radiation-induced urgency syndrome’ in order to derive the corresponding dose–response relationships as an aid for avoiding the syndrome in the future.</p> <p><b>Material and methods:</b> From a larger group of gynecological cancer survivors followed-up 2–14 years, we identified 98 whom had undergone external beam radiation therapy but not brachytherapy and not having a stoma. Of those survivors, 24 developed urgency syndrome. Based on the loading factor from a factor analysis, and symptom frequency, 15 symptoms were weighted together to a score interpreted as the intensity of radiation-induced urgency symptom. On reactivated dose plans, we contoured the small intestine, sigmoid colon and the rectum (separate from the anal-sphincter region) and we exported the dose-volume histograms for each survivor. Dose–response relationships from respective risk organ and urgency syndrome were estimated by fitting the data to the Probit, RS, LKB and gEUD models.</p> <p><b>Results:</b> The rectum and sigmoid colon have steep dose–response relationships for urgency syndrome for Probit, RS and LKB. The dose–response parameters for the rectum were <i>D<sub>50</sub></i><sub>:</sub> 51.3, 51.4, and 51.3 Gy, <i>γ<sub>50</sub></i> = 1.19 for all models, <i>s</i> was 7.0e<sup>−09</sup> for RS and <i>n</i> was 9.9 × 10<sup>7</sup> for LKB. For Sigmoid colon, <i>D<sub>50</sub></i> were 51.6, 51.6, and 51.5 Gy, <i>γ<sub>50</sub></i> were 1.20, 1.25, and 1.27, <i>s</i> was 2.8 for RS and <i>n</i> was 0.079 for LKB.</p> <p><b>Conclusions:</b> Primarily the dose to sigmoid colon as well as the rectum is related to urgency syndrome among gynecological cancer survivors. Separate delineation of the rectum and sigmoid colon in order to incorporate the dose–response results may aid in reduction of the incidence of the urgency syndrome.</p
The estimated factor loadings onto the six factors after the Varimax rotation was performed.
<p>Factor loadings are colored according to factor affiliation and are connected by solid lines of the corresponding color. Dashed horizontal lines correspond to the factor specific cutoffs suggested by the Variable Cutoff Method. Crosses of a specific color correspond to factor loadings strictly greater in magnitude than the cutoff of the same color whereas solid dots of a specific color correspond to factor loadings smaller in magnitude than the cutoff of the corresponding color. Using the Variable Cutoff Method 10000 parametric bootstrap estimates of the factor loadings were calculated and 0,0.01,…,0.99,1 were used as candidate cutoffs.</p
Comparisons between estimated factor score quantile positions of survivors and controls for the six factors.
<p>The 0.25, 0.5 (median), 0.75, 0.9 and 0.95 sample quantiles are presented. Scores were calculated based on the reduced factor loading structure. Prior to calculating scores a simple mode imputation was performed. Further Mann-Whitney p-values were calculated and are presented to the left in the figure. Except in the case of the constipation factor, the factor scores of the treated population were found to be distributed significantly differently from the scores of the non-treated population. Clearly, in all cases where these distributions differ, the scores of the survivors tend to be larger than the scores of the controls.</p
Estimated factor loading structure and factor model properties.
<p>Estimated factor loading structure and factor model properties.</p
The result of applying the cutoffs suggested by the Variable Cutoff Method to the estimated factor loadings onto the six factors.
<p>Dots correspond to factor loadings that are strictly greater in magnitude than the factor specific cutoff. Lines through the dots correspond to the magnitude of the specific factor loadings and are presented for comparison purposes only with the aim of identifying the variables that most heavily load onto a specific factor and thus to aid interpretation. The plot illustrates how cutoffs on factor loadings ease the interpretation of the factor loading structure produced by EFA. Several factor loadings are discarded by the Variable cutoff method. Based on this reduced factor loading structures the six factors were interpreted as: Urgency syndrome (red), Leakage syndrome (green), Constipation (dark blue), Excessive gas discharge (light blue), Excessive mucus discharge (magenta), Blood discharge (black).</p