Risk factor analysis and nomogram construction for predicting suicidal ideation in patients with cancer

Identification of symptom clusters and sentinel symptoms during the first cycle of chemotherapy in patients with lung cancer

PURPOSE

To identify symptom clusters (SCs) in patients with lung cancer who are undergoing initial chemotherapy and to identify the sentinel symptoms of each SC.

METHODS

A convenience sampling method was used to recruit patients with lung cancer who were undergoing their initial chemotherapy treatment. Patient information was collected using the General Demographic Questionnaire, MD Anderson Symptom Inventory (including the lung cancer module) and a schedule documenting the initial occurrence of symptoms. The Walktrap algorithm was employed to identify SCs, while sentinel symptoms within each SC were identified using the Apriori algorithm in conjunction with the initial occurrence time of symptoms.

RESULTS

A total of 169 patients with lung cancer participated in this study, and four SCs were identified: the psychological SC (difficulty remembering, sadness, dry mouth, numbness or tingling, and distress), somatic SC (pain, fatigue, sleep disturbance, and drowsiness), respiratory SC (coughing, expectoration, chest tightness, and shortness of breath), and digestive SC (nausea, poor appetite, constipation, vomiting, and weight loss). Sadness, fatigue, and coughing were identified as sentinel symptoms of the psychological, somatic, and respiratory SCs, respectively. However, no sentinel symptom was identified for the digestive SC.

CONCLUSION

Patients with lung cancer who are undergoing chemotherapy encounter a spectrum of symptoms, often presenting as SCs. The sentinel symptom of each SC emerges earlier than the other symptoms and is characterized by its sensitivity, significance, and driving force. It serves as a vital indicator of the SC and assumes a sentry role. Targeting sentinel symptoms might be a promising strategy for determining the optimal timing of interventions and for mitigating or decelerating the progression of the other symptoms within the SC.

To what extent are psychological variables considered in the study of risk and protective factors for suicidal thoughts and behaviours in individuals with cancer? A systematic review of 70 years of research

Psychological variables substantially shape the risk of suicidal thoughts and behaviours (STBs). However, it is unclear to what extent they are considered in individuals with cancer. We synthesized the quantitative research landscape concerning psychological risk/protective factors of STBs in the (psycho-) oncological context. This pre-registered review (PROSPERO-ID CRD42022331484) systematically searched the databases PubMed/Medline, CINAHL, PsycInfo, Cochrane Library, and Web of Science (as well as the grey literature and preprints). Risk of bias (RoB) was estimated using the ROBINS-I tool. Of 11,159 retrieved records, 319 studies were eligible for inclusion. Of those, 163 (51.1%) had investigated psychological factors (affective: n = 155; social: n = 65; cognitive: n = 63; personality/individual differences: n = 37; life events: n = 6), in a combined 3,561,741 participants. The most common STBs were suicidal ideation (n = 107) or death wishes (n = 20) rather than behaviour (suicide deaths: n = 26; attempts: n = 14). Most studies had a serious RoB. Thus, a large body of research investigated STBs in cancer patients/survivors, but it rarely aligned with the theoretical or clinical developments in suicide research. We propose a conceptual model of STBs in cancer delineating moderation and mediation effects to advance the integration of the fields, and to inform future research and practice.

Analysis of risk factors of suicidal ideation in adolescent patients with depression and construction of prediction model

BACKGROUND

Major depressive disorder is a common mental illness among adolescents and is the largest disease burden in this age group. Most adolescent patients with depression have suicidal ideation (SI); however, few studies have focused on the factors related to SI, and effective predictive models are lacking.

AIM

To construct a risk prediction model for SI in adolescent depression and provide a reference assessment tool for prevention.

METHODS

The data of 150 adolescent patients with depression at the First People's Hospital of Lianyungang from June 2020 to December 2022 were retrospectively analyzed. Based on whether or not they had SI, they were divided into a SI group (n = 91) and a non-SI group (n = 59). The general data and laboratory indices of the two groups were compared. Logistic regression was used to analyze the factors influencing SI in adolescent patients with depression, a nomogram prediction model was constructed based on the analysis results, and internal evaluation was performed. Receiver operating characteristic and calibration curves were used to evaluate the model's efficacy, and the clinical application value was evaluated using decision curve analysis (DCA).

RESULTS

There were differences in trauma history, triggers, serum ferritin levels (SF), high-sensitivity C-reactive protein levels (hs-CRP), and high-density lipoprotein (HDL-C) levels between the two groups (P < 0.05). Logistic regression analysis showed that trauma history, predisposing factors, SF, hs-CRP, and HDL-C were factors influencing SI in adolescent patients with depression. The area under the curve of the nomogram prediction model was 0.831 (95%CI: 0.763-0.899), sensitivity was 0.912, and specificity was 0.678. The higher net benefit of the DCA and the average absolute error of the calibration curve were 0.043, indicating that the model had a good fit.

CONCLUSION

The nomogram prediction model based on trauma history, triggers, ferritin, serum hs-CRP, and HDL-C levels can effectively predict the risk of SI in adolescent patients with depression.

Preoperative blood markers and intra-abdominal infection after colorectal cancer resection

BACKGROUND

Colorectal cancer (CRC) has one of the highest morbidity and mortality rates among digestive tract tumors. Intra-abdominal infection (IAI) is a common postoperative complication that affects the clinical outcomes of patients with CRC and hinders their rehabilitation process. However, the factors influencing abdominal infection after CRC surgery remain unclear; further, prediction models are rarely used to analyze preoperative laboratory indicators and postoperative complications.

AIM

To explore the predictive value of preoperative blood markers for IAI after radical resection of CRC.

METHODS

The data of 80 patients who underwent radical resection of CRC in the Anorectal Surgery Department of Suzhou Hospital affiliated with Anhui Medical University were analyzed. These patients were categorized into IAI (n = 15) and non-IAI groups (n = 65) based on whether IAI occurred. Influencing factors were compared; general data and laboratory indices of both groups were identified. The relationship between the indicators was assessed. Further, a nomogram prediction model was developed and evaluated; its utility and clinical applicability were assessed.

RESULTS

The risk factors for IAI after radical resection of CRC were neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and carcinoembryonic antigen (CEA) levels. NLR was correlated with PLR and SII (r = 0.604, 0.925, and 0.305, respectively), while PLR was correlated with SII (r = 0.787). The nomogram prediction model demonstrated an area under the curve of 0.968 [95% confidence interval (CI): 0.948-0.988] in the training set (n = 60) and 0.926 (95%CI: 0.906-0.980) in the validation set (n = 20). The average absolute errors of the calibration curves for the training and validation sets were 0.032 and 0.048, respectively, indicating a good model fit. The decision curve analysis curves demonstrated high net income above the 5% threshold, indicating the clinical practicality of the model.

CONCLUSION

The nomogram model constructed using NLR, PLR, SII, and CEA levels had good accuracy and reliability in predicting IAI after radical resection of CRC, potentially aiding clinical treatment decision-making.

Risk factors associated with suicidal ideation among cancer patients: a systematic review and meta-analysis

Objective

The objective of this review was to provide a comprehensive summary and analysis of the risk factors associated with suicidal ideation among cancer patients.

Methods

This review adhered to the PICO/S framework and guidelines outlined in the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) framework (PROSPERO CRD42023433639). We searched Web of Science, PubMed, Embase, Scopus, PsycINFO, and Cochrane Library from the establishment date of the databases until June 9, 2023 for observational studies that reveal risk factors associated with suicidal ideation among cancer patients. Software Review Manager 5 (vision 5.4) was used for Meta-analyses.

Results

4,921 studies were obtained through the search of the databases, 40 of which were eligible. Meta-analysis revealed that suicidal ideation in cancer patients was significantly associated with marital status, living alone, post-traumatic stress disorder (PTSD), panic disorder, education, psychiatric illness history, social functioning, childhood adversity experience, financial problems, pain, depression, demoralization, vomiting, residence and anxiety.

Conclusion

Being unmarried, living alone, less educated, living in rural, financial problems, pain, vomiting, PTSD, psychiatric illness history, lower social functioning, childhood adversity experience, anxiety, depression, demoralization, panic disorder were risk factors for suicidal ideation among cancer patients. This review provided evidence-based information for identifying and reducing the risk of suicide in cancer survivors.Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, CRD42023433639.

Identification of risk factors for attempted suicide by self-poisoning and a nomogram to predict self-poisoning suicide

Purpose

Suicide is a global concern, especially among young people. Suicide prediction models have the potential to make it easier to identify patients who are at a high risk of suicide, but they have very little predictive power when there is a positive value for suicide mortality. Therefore, the aim of the study is to uncover potential risk factors associated with suicide by self-poisoning and further to provide a trustworthy nomogram to predict self-poisoning suicide among poisoned patients.

Methods

This study prospectively enrolled 237 patients who were treated for poisoning at the Fifth Medical Center of PLA General Hospital (Beijing) between May 2021 and May 2022. Patient's basic characteristics, daily activities, mental health status, and history of psychological illnesses were gathered to examine their predictive power for self-poisoning suicide. On developing a prediction model, patients were split 8:2 into a training (n = 196) group and a validation (n = 41) group at random via computer. The training group worked on model development, while the validation group worked on model validation. In this study, the Hosmer and Lemeshow test, accuracy, and area under the curve were the primary evaluation criteria. Shapley Additive exPlanations (SHAP) was determined to evaluate feature importance. To make the prediction model easy for researchers to utilize, it was presented in nomogram format. Two risk groups of patients were identified based on the ideal cut-off value.

Results

Of all poisoned patients, 64.6% committed suicide by self-poisoning. With regard to self-poisoning attempted suicide, multivariate analysis demonstrated that female gender, smoking, generalized anxiety disorder-7 (GAD-7), and beck hopelessness scale-20 (BHS-20) were significant risk factors, whereas married status, relatively higher education level, a sedentary time of 1–3 h per day, higher sport frequency per week, higher monthly income were significant protective features. The nomogram contained each of the aforementioned nine features. In the training group, the area under curve (AUC) of the nomogram was up to 0.938 (0.904–0.972), whereas in the validation group, it reached a maximum of 0.974 (0.937–1.000). Corresponding accuracy rates were up to 0.883 and 0.927, respectively, and the P-values for the Hosmer and Lemeshow test were 0.178 and 0.346, respectively. SHAP demonstrated that the top three most important features were BHS-20, GAD-7, and marital status. Based on the best cut-off value of the nomogram (40%), patients in the high-risk group had a nearly six-time larger likelihood of committing suicide by self-poisoning than patients in the low-risk group (88.68 vs. 15.38%, P &lt; 0.001). The dynamic nomogram was made available at the following address: https://xiaobo.shinyapps.io/Nomogramselfpoisoningsuicide/.

Conclusions

This study proposes a prediction model to stratify patients at a high risk of suicide by self-poisoning and to guide individual preventive strategies. Patients in the high-risk group require further mental health counseling to alleviate anxiety and hopelessness, healthy lifestyle like quitting smoking and exercising more, and restriction of access to poison and psychiatric drugs.

Impact of alexithymia on suicidal ideation among patients with ovarian cancer: a moderated mediation model of self-perceived burden and general self-efficacy

PURPOSE

Suicidal ideation (SI) and alexithymia are common psychological problems among patients with cancer. Studying how alexithymia predicts SI is helpful for its intervention and prevention strategies. The present study aimed to investigate whether self-perceived burden (SPB) mediates the impact of alexithymia on SI and if general self-efficacy moderates the associations of alexithymia with SPB and SI.

METHODS

To measure SI, alexithymia, SPB, and general self-efficacy, 200 patients with ovarian cancer at all stages regardless of the type of treatment completed the Chinese version of the Self-Rating Idea of Suicide Scale, Toronto Alexithymia Scale, Self-Perceived Burden Scale, and General Self-Efficacy Scale in a cross-sectional study. The PROCESS macro for SPSS v4.0 procedure was applied to perform moderated mediation analysis.

RESULTS

SPB significantly mediated the positive impact of alexithymia on SI (a×b = 0.082, 95% confidence interval [CI]: 0.026, 0.157). General self-efficacy significantly moderated the positive association between alexithymia and SPB (β = -0.227, P < 0.001). The mediating role of SPB was gradually reduced as general self-efficacy grew (low: 0.087, 95% CI: 0.010, 0.190; medium: 0.049, 95% CI: 0.006, 0.108; high: 0.010, 95% CI: -0.014, 0.046). Thus, a moderated mediation model involving SPB and general self-efficacy for explaining how alexithymia causes SI was supported.

CONCLUSION

Alexithymia could cause SI by inducing SPB among patients with ovarian cancer. General self-efficacy could attenuate the association between alexithymia and SPB. Interventions aimed at reducing SPB and enhancing general self-efficacy could reduce SI by partially preventing and attenuating the impact of alexithymia.

Symptom distress and suicidal ideation among Chinese ovarian cancer patients: A moderated mediation model of depression and suicide resilience

Objective

The aim of this study was to examine whether depression mediates the relationship between symptom distress and suicidal ideation in Chinese patients with ovarian cancer, and whether this mediating effect was moderated by suicide resilience.

Methods

From March to October 2022, this cross-sectional study was performed in a three Grade 3A hospital and an oncology specialty hospital in Wuhan, Hubei Province, China. Ultimately, 213 ovarian cancer patients completed anonymous self-report. Bootstrapping method was used for regression analysis to test the mediating and moderating effects.

Results

Among the 213 participants, 29.58% (n = 63) exhibited significant suicidal ideation. Symptom distress was positively associated with suicidal ideation, and depression partially mediated this relationship. Suicide resilience moderated the relationship between depression and suicidal ideation. In ovarian cancer patients with low suicide resilience, the effect of symptom distress on suicidal ideation through depression was greater, while in patients with high suicide resilience, this effect was attenuated.

Conclusion

Our study suggests that symptom distress could be more likely to lead to suicidal ideation as depression levels increase in ovarian cancer patients. Fortunately, suicide resilience could attenuate this negative effect.

A nomogram of suicidal ideation among men who have sex with men in China: Based on the integrated motivational-volitional model of suicidal behavior

Introduction

Men who have sex with men (MSM) are a high-risk group for suicide, with a much higher prevalence of suicidal ideation (SI) than the general population and male population. The aim of this study was to explore the risk factors influencing the development of SI and to develop and validate a nomogram among MSM.

Methods

A cross-sectional study was conducted in 915 MSM from Shanghai, Shenyang, Shenzhen and Kunming, China using the snowball sampling method. The integrated motivational-volitional (IMV) model of suicidal behavior was used as a theoretical framework to collect different potential influencing factors of SI including diathesis-environment-life events factors and psychosocial factors. The risk factors of SI were screened by logistic regression analysis, and a nomogram for predicting SI were developed. Model properties including discrimination, calibration and decision curves were evaluated to validate the prediction model.

Results

882 MSM were included in the statistical analysis, with a lifetime prevalence of SI of 34.4% (303/882). Logistic regression analysis showed that age group, sexual orientation disclosure, high-risk sexual behavior, entrapment, defeat and interpersonal needs were associated with SI. A nomogram was constructed based on the above six predictors. AUC values of ROC for prediction model were 0.761 (0.641-0.770) and 0.754 (0.565-0.822) in the training set (n = 662) and validation set (n = 220), respectively. And there was no statistical difference of the AUC values between the two sets (P > 0.05). The calibration plots of the prediction model in both sets fit well with the ideal model (P > 0.05). The decision curves demonstrated that the threshold probability of prediction model in training set was 1-85%, whereas in validation set was 1-63%.

Conclusions

The lifetime prevalence of SI among Chinese MSM is high. The nomogram can serve as a useful tool to predict the development of SI among MSM. Defeat, entrapment and interpersonal needs, as significant predictors of SI, can be measured to identify SI in advance. Early assessment of SI and the enhancement of psychosocial interventions are important to prevent suicide-related behaviors. Future studies could incorporate more variables of interest to refine the prediction model to better guide behavioral and psychological intervention strategies among MSM.

Suicide risk among female breast cancer survivors: A population-based study

Background

Breast cancer is the most common cancer type for females and has the highest relative number of suicide cases among female-specific cancers. This study aimed to demonstrate suicide rates and changing trends and to identify risk factors for suicide among female breast cancer survivors.

Methods

Data were derived from the surveillance, epidemiology, and end results database for women diagnosed with breast cancer from 2000 to 2017. Mortality rate and standardized mortality ratios (SMRs) were calculated to describe the incidence rate and trend of suicide among female breast cancer survivors. Gray's test and cumulative incidence function (CIF) curves were used to assess difference of cumulative suicide incidence in subgroups. Multivariate Fine-Gray competing risk model was used to identify risk factors for individual survivors and nomogram model was used to estimate the probability of suicide.

Result

There were 414 suicide cases among 638,547 female breast cancer survivors observed for 5,079,194 person-years, and the suicide rate and SMRs gradually increased with the year of diagnosis. Female breast cancer survivors had a higher risk of suicide than the general population (SMR = 1.19; 95% CI (1.08-1.31)). Based on the result of Fine-Gray competing risk models, age group (50-70 vs <50: HR=0.65, 95% CI:0.52-0.80; >70 vs <50: HR=0.22, 95% CI:0.15-0.32), race/ethnicity (black vs white: HR= 0.20, 95% CI: 0.11-0.36; other race vs white: HR= 0.67, 95% CI: 0.46-0.97), marital status (separated vs married: HR= 1.50, 95% CI: 1.16-1.94; single vs married: HR= 1.70, 95% CI: 1.31-2.20), stage (distant vs regional: HR= 0.30, 95% CI: 0.14-0.63), radiotherapy (Yes vs No/Unknown: HR= 0.62, 95% CI: 0.49-0.77), and molecular subtypes (HER-2 vs Luminal B (HR= 2.53, 95% CI: 1.10-5.82), TNBC vs Luminal B (HR= 2.11, 95% CI: 1.01-4.42)) were independent predictors of suicide among female breast cancer patients. A nomogram was constructed to predict the suicide probability for individual survivors with a C-index of 0.62 (95%CI: 0.59-0.66).

Conclusion

Female breast cancer survivors with younger age (less than 50 years old), white race, unmarried status, regional stage, HER-2 or TNBC subtype, and no radiotherapy performed were more likely to commit suicide. The clinicians and family members should pay more attention to patients with high risk factors of suicide to decrease the mortality rate.