Identifying radiation-induced survivorship syndromes affecting bowel health in a cohort of gynecological cancer survivors

Abstract

Background: During radiotherapy unwanted radiation to normal tissue surrounding the tumor triggers survivorship diseases; we lack a nosology for radiation-induced survivorship diseases that decrease bowel health and we do not know which symptoms are related to which diseases.

Methods: Gynecological-cancer survivors were followed-up two to 15 years after having undergone radiotherapy; they reported in a postal questionnaire the frequency of 28 different symptoms related to bowel health. Population-based controls gave the same information. With a modified factor analysis, we determined the optimal number of factors, factor loadings for each symptom, factor-specific factor-loading cutoffs and factor scores.

Results: Altogether data from 623 survivors and 344 population-based controls were analyzed. Six factors best explain the correlation structure of the symptoms; for five of these a statistically significant difference (P< 0.001, Mann-Whitney U test) was found between survivors and controls concerning factor score quantiles. Taken together these five factors explain 42 percent of the variance of the symptoms. We interpreted these five factors as radiation-induced syndromes that may reflect distinct survivorship diseases. We obtained the following frequencies, defined as survivors having a factor loading above the 95 percent percentile of the controls, urgency syndrome (190 of 623, 30 percent), leakage syndrome (164 of 623, 26 percent), excessive gas discharge (93 of 623, 15 percent), excessive mucus discharge (102 of 623, 16 percent) and blood discharge (63 of 623, 10 percent).

Conclusion: Late effects of radiotherapy include five syndromes affecting bowel health; studying them and identifying the underlying survivorship diseases, instead of the approximately 30 long-term symptoms they produce, will simplify the search for prevention, alleviation and elimination.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1. The estimated factor loadings onto the six factors after the Varimax rotation was performed.

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.

Fig 2. The result of applying the cutoffs suggested by the Variable Cutoff Method to the estimated factor loadings onto the six factors.

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).

Fig 3. Comparisons between estimated factor score quantile positions of survivors and controls for the six factors.

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.