Nonlinear Predictive Models for Multiple Mediation Analysis: With an Application to Explore Ethnic Disparities in Anxiety and Depression Among Cancer Survivors

Tools to assess employment readiness for colorectal cancer survivors: A scoping review

BACKGROUND

The ability to return to work and remain at work is an important recovery milestone after a cancer diagnosis. With the projected number of colorectal cancer patients of working age likely to increase, it is important to identify when a person is ready to resume work. There are many employment-related tools available to help people return to work after injury or illness; however, it is unknown which may be suitable for a person with colorectal cancer.

AIM

To identify tools related to employment readiness in colorectal cancer survivors and to chart the relevant factors of employment assessed by these tools.

METHOD

Literature searches were performed in PubMed, CINAHL, Embase and Medline, the Cochrane library and PsycINFO using search terms around cancer, survivorship and employment to identify all peer-reviewed articles published in English up to June 2022.

RESULTS

Thirty-five studies used a total of 77 tools focused on assessing employment issues experienced by people with cancer in general. Four tools were used with colorectal cancer survivors. None considered all relevant employment-related factors for colorectal cancer survivors.

CONCLUSION

Tools used to identify return-to-work and remain-at-work were not specific to colorectal cancer. There are a range of existing tools that collate some, but not all, of the domains and outcome criteria required to meet the employment needs of colorectal cancer survivors. To optimize work outcomes for the working colorectal cancer population, a specified tool is warranted.

Risk of coronary heart disease in patients with periodontitis among the middled-aged and elderly in China: a cohort study

BACKGROUND

Convincing evidence of the periodontitis as a risk factor for coronary heart disease (CHD) is lacking due to shared risk factors, and no cohort study has investigated the association between CHD and periodontitis in Chinese populations.

METHODS

This study used a prospective cohort study design. The analysis included 4591 participants aged 40 years and older (3146 men and 1445 women). The association between CHD and periodontitis was estimated using relative risk (RR) calculated using modified Poisson regression. Multiple mediation analysis was used to differentiate the relative effects (RE) from different risk factors on the effect of periodontitis on CHD.

RESULTS

In the analysis using the imputed dataset and fully adjusted model, participants with periodontitis at baseline had 37% increased risk of CHD overall compared to those without periodontitis at baseline (RR 1.37; 95% CI 0.96-1.95). Most of the association can be explained by age, sex, history of diabetes, history of hypertension, uric acid and education (RE 0.76; 95% CI 0.41-1.02).

CONCLUSION

Periodontitis was weakly associated with an increased risk of CHD among the middled-aged and elderly in China. Further studies are required to identify more mediators and elucidate the mechanisms of how periodontitis increases the risk of CHD.

Differential Item Functioning Analyses of the Patient-Reported Outcomes Measurement Information System (PROMIS®) Measures: Methods, Challenges, Advances, and Future Directions

Several methods used to examine differential item functioning (DIF) in Patient-Reported Outcomes Measurement Information System (PROMIS®) measures are presented, including effect size estimation. A summary of factors that may affect DIF detection and challenges encountered in PROMIS DIF analyses, e.g., anchor item selection, is provided. An issue in PROMIS was the potential for inadequately modeled multidimensionality to result in false DIF detection. Section 1 is a presentation of the unidimensional models used by most PROMIS investigators for DIF detection, as well as their multidimensional expansions. Section 2 is an illustration that builds on previous unidimensional analyses of depression and anxiety short-forms to examine DIF detection using a multidimensional item response theory (MIRT) model. The Item Response Theory-Log-likelihood Ratio Test (IRT-LRT) method was used for a real data illustration with gender as the grouping variable. The IRT-LRT DIF detection method is a flexible approach to handle group differences in trait distributions, known as impact in the DIF literature, and was studied with both real data and in simulations to compare the performance of the IRT-LRT method within the unidimensional IRT (UIRT) and MIRT contexts. Additionally, different effect size measures were compared for the data presented in Section 2. A finding from the real data illustration was that using the IRT-LRT method within a MIRT context resulted in more flagged items as compared to using the IRT-LRT method within a UIRT context. The simulations provided some evidence that while unidimensional and multidimensional approaches were similar in terms of Type I error rates, power for DIF detection was greater for the multidimensional approach. Effect size measures presented in Section 1 and applied in Section 2 varied in terms of estimation methods, choice of density function, methods of equating, and anchor item selection. Despite these differences, there was considerable consistency in results, especially for the items showing the largest values. Future work is needed to examine DIF detection in the context of polytomous, multidimensional data. PROMIS standards included incorporation of effect size measures in determining salient DIF. Integrated methods for examining effect size measures in the context of IRT-based DIF detection procedures are still in early stages of development.

Multilevel mediation analysis on time-to-event outcomes: Exploring racial/ethnic disparities in breast cancer survival in California

Background

Third-variable effect refers to the effect from a third-variable that explains an observed relationship between an exposure and an outcome. Depending on whether there is a causal relationship from the exposure to the third variable, the third-variable is called a mediator or a confounder. The multilevel mediation analysis is used to differentiate third-variable effects from data of hierarchical structures.

Data Collection and Analysis

We developed a multilevel mediation analysis method to deal with time-to-event outcomes and implemented the method in the mlma R package. With the method, third-variable effects from different levels of data can be estimated. The method uses multilevel additive models that allow for transformations of variables to take into account potential nonlinear relationships among variables in the mediation analysis. We apply the proposed method to explore the racial/ethnic disparities in survival among patients diagnosed with breast cancer in California between 2006 and 2017, using both individual risk factors and census tract level environmental factors. The individual risk factors are collected by cancer registries and the census tract level factors are collected by the Public Health Alliance of Southern California in partnership with the Virginia Commonwealth University's Center on Society and Health. The National Cancer Institute work group linked variables at the census tract level with each patient and performed the analysis for this study.

Results

We found that the racial disparity in survival were mostly explained at the census tract level and partially explained at the individual level. The associations among variables were depicted. Conclusion: The multilevel mediation analysis method can be used to differentiate mediation/confounding effects for factors originated from different levels. The method is implemented in the R package mlma.

Quantifying Mediators of Racial Disparities in Knee Osteoarthritis Outcome Scores: A Cross-Sectional Analysis

Studies on symptomatic osteoarthritis suggest that Black patients report worse pain and symptoms compared with White patients with osteoarthritis. In this study, we aimed to quantify the relationship among variables such as overall health and socioeconomic status that may contribute to disparities in patient-reported outcomes.

What mediates the racial/ethnic disparity in psychosocial stress among breast cancer patients?

BACKGROUND

Prior studies have observed greater levels of psychosocial stress (PSS) among non-Hispanic (nH) African American and Hispanic women when compared to nH White patients after a breast cancer diagnosis. We aimed to determine the independent and interdependent roles of socioeconomic position (SEP) and unmet support in the racial disparity in PSS among breast cancer patients.

METHODS

Participants were recruited from the Breast Cancer Care in Chicago study (n = 989). For all recently diagnosed breast cancer patients, aged 25-79, income, education, and tract-level disadvantage and affluence were summed to create a standardized socioeconomic position (SEP) score. Three measures of PSS related to loneliness, perceived stress, and psychological consequences of a breast cancer diagnosis were defined based on previously validated scales. Five domains of unmet social support needs (emotional, spiritual, informational, financial, and practical) were defined from interviews. We conducted path models in MPlus to estimate the extent to which PSS disparities were mediated by SEP and unmet social support needs.

RESULTS

Black and Hispanic patients reported greater PSS compared to white patients and greater unmet social support needs (p = 0.001 for all domains). Virtually all of the disparity in PSS could be explained by SEP. A substantial portion of the mediating influence of SEP was further transmitted by unmet financial and practical needs among Black patients and by unmet emotional needs for Hispanic patients.

CONCLUSIONS

SEP appeared to be a root cause of the racial/ethnic disparities in PSS within our sample. Our findings further suggest that different interventions may be necessary to alleviate the burden of SEP for nH AA (i.e., more financial support) and Hispanic patients (i.e., more emotional support).

Social Network Mediation Analysis: A Latent Space Approach

A social network comprises both actors and the social connections among them. Such connections reflect the dependence among social actors, which is essential for individuals' mental health and social development. In this article, we propose a mediation model with a social network as a mediator to investigate the potential mediation role of a social network. In the model, the dependence among actors is accounted for by a few mutually orthogonal latent dimensions which form a social space. The individuals' positions in such a latent social space are directly involved in the mediation process between an independent and dependent variable. After showing that all the latent dimensions are equivalent in terms of their relationship to the social network and the meaning of each dimension is arbitrary, we propose to measure the whole mediation effect of a network. Although individuals' positions in the latent space are not unique, we rigorously articulate that the proposed network mediation effect is still well defined. We use a Bayesian estimation method to estimate the model and evaluate its performance through an extensive simulation study under representative conditions. The usefulness of the network mediation model is demonstrated through an application to a college friendship network.

Third-variable effect analysis with multilevel additive models

Third-variable effect refers to the effect transmitted by third-variables that intervene in the relationship between an exposure and a response variable. Third-variable effect analysis has been broadly studied in many fields. However, it remains a challenge for researchers to differentiate indirect effect of individual factor from multiple third-variables, especially when the involving variables are of hierarchical structure. Yu et al. (2014) defined third-variable effects that were consistent for all different types of response (categorical or continuous), exposure, or third-variables. With these definitions, multiple third-variables can be considered simultaneously, and the indirect effects carried by individual third-variables can be separated from the total effect. In this paper, we extend the definitions of third-variable effects to multilevel data structures, where multilevel additive models are adapted to model the variable relationships. And then third-variable effects can be estimated at different levels. Moreover, transformations on variables are allowed to present nonlinear relationships among variables. We compile an R package mlma, to carry out the proposed multilevel third-variable analysis. Simulations show that the proposed method can effectively differentiate and estimate third-variable effects from different levels. Further, we implement the method to explore the racial disparity in body mass index accounting for both environmental and individual level risk factors.

Calidad de Vida: a systematic review of quality of life in Latino cancer survivors in the USA

BACKGROUND

Cancer is the leading cause of death among Hispanics/Latinos. Thus, understanding health-related quality of life (HRQOL) needs among this diverse racial/ethnic group is critical. Using Ferrell's multidimensional framework for measuring QOL, we synthesized evidence on HRQOL needs among Hispanic/Latino cancer survivors.

METHODS

We searched MEDLINE/PubMed, EMBASE, CINAHL, and PsycINFO, for English language articles published between 1995 and January 2020, reporting HRQOL among Hispanic/Latino cancer survivors in the USA.

RESULTS

Of the 648 articles reviewed, 176 met inclusion criteria, with 100 of these studies focusing exclusively on breast cancer patients and no studies examining end-of-life HRQOL issues. Compared with other racial/ethnic groups, Hispanics/Latinos reported lower HRQOL and a higher symptom burden across multiple HRQOL domains. Over 80% of studies examining racial/ethnic differences in psychological well-being (n = 45) reported worse outcomes among Hispanics/Latinos compared with other racial/ethnic groups. Hispanic/Latino cancer survivors were also more likely to report suboptimal physical well-being in 60% of studies assessing racial/ethnic differences (n = 27), and Hispanics/Latinos also reported lower social well-being relative to non-Hispanics/Latinos in 78% of studies reporting these outcomes (n = 32). In contrast, reports of spiritual well-being and spirituality-based coping were higher among Hispanics/Latinos cancer survivors in 50% of studies examining racial/ethnic differences (n = 15).

DISCUSSION

Findings from this review point to the need for more systematic and tailored interventions to address HRQOL needs among this growing cancer survivor population. Future HRQOL research on Hispanics/Latinos should evaluate variations in HRQOL needs across cancer types and Hispanic/Latino subgroups and assess HRQOL needs during metastatic and end-of-life disease phases.

A Multivariate Multiple Third-Variable Effect Analysis with an Application to Explore Racial and Ethnic Disparities in Obesity

Third-Variable effect refers to the intervening effect from a third variable (called mediators or confounders) to the observed relationship between an exposure and an outcome. The general multiple third-variable effect analysis method (TVEA) allows consideration of multiple mediators/confounders (MC) simultaneously and the use of linear and non-linear predictive models for estimating MC effects. Previous studies have found that compared with non-Hispanic White population, Blacks and Hispanic Whites suffered disproportionally more with obesity and related chronic diseases. In this paper, we extend the general TVEA to deal with multivariate/multicategorical predictors and multivariate response variables. We designed algorithms and an R package for this extension and applied MMA on the NHANES data to identify MCs and quantify the indirect effect of each MC in explaining both racial and ethnic disparities in obesity and the body mass index (BMI) simultaneously. We considered a number of socio-demographic variables, individual factors, and environmental variables as potential MCs and found that some of the ethnic/racial differences in obesity and BMI were explained by the included variables.

Role of lymphadenectomy, adjuvant chemotherapy, and treatment at high-volume centers in patients with resected pancreatic cancer-a distinct view on lymph node yield

PURPOSE

While the importance of lymphadenectomy is well-established for patients with resectable pancreatic cancer, its direct impact on survival in relation to other predictive factors is still ill-defined.

METHODS

The National Cancer Data Base 2006-2015 was queried for patients with resected pancreatic adenocarcinoma (stage IA-IIB). Patients were dichotomized into the following two groups, those with 1-14 resected lymph nodes and those with ≥ 15. Optimal number of resected lymph nodes and the effect of lymphadenectomy on survival were assessed using various statistical modeling techniques. Mediation analysis was performed to differentiate the direct and indirect effect of lymph node resection on survival.

RESULTS

A total of 21,912 patients were included; median age was 66 years (IQR 59-73), 48.9% were female. Median number of resected lymph nodes was 15 (IQR 10-22), 10,163 (46.4%) had 1-14 and 11,749 (53.6%) had ≥ 15 lymph nodes retrieved. Lymph node positivity increased by 4.1% per lymph node up to eight examined lymph nodes, and by 0.6% per lymph node above eight. Five-year overall survival was 17.9%. Overall survival was better in the ≥ 15 lymph node group (adjusted HR 0.91, CI 0.88-0.95, p < 0.001). On a continuous scale, survival improved with increasing LNs collected. Patients who underwent adjuvant chemotherapy and were treated at high-volume centers had improved overall survival compared with their counterparts (adjusted HR 0.59, CI 0.57-0.62, p < 0.001; adjusted HR 0.86, CI 0.83-0.89, p < 0.001, respectively). Mediation analysis revealed that lymphadenectomy had only 18% direct effect on improved overall survival, while 82% of its effect were mediated by other factors like treatment at high-volume hospitals and adjuvant chemotherapy.

DISCUSSION

While higher number of resected lymph nodes increases lymph node positivity and is associated with better overall survival, most of the observed survival benefit is mediated by chemotherapy and treatment at high-volume centers.

Meaning-Centered Psychotherapy for Latino Patients with Advanced Cancer: Cultural Adaptation Process

Background: Latino patients with advanced cancer need culturally responsive, effective psychotherapeutic interventions that can assist them in coping with their diagnosis and improve spiritual and existential well-being and psychological adjustment. Objective: This study describes the cultural and linguistic adaptation of individual meaning-centered psychotherapy for Latinos with advanced cancer. Design: A mixed-methods, concurrent integrative approach was used for this study, using the ecological validity and cultural adaptation process models as frameworks for cultural adaptation. Setting/Subjects and Measurements: Quantitative and qualitative data were collected through (1) a survey of mental health professionals (n = 70) who offer services to Latino cancer patients; (2) a questionnaire for Latino patients with advanced cancer (n = 54), measuring relevant intervention concepts; and (3) in-depth interviews with 24 Latino patients. Results: Quantitative findings showed that most of the goals and concepts were highly acceptable for patients and providers. The qualitative findings supported adaptations to include using more simple definitions; changing phrases that are challenging to translate and comprehend; using words that are common to all Latino cultures, providing more than one option if needed; simplifying the questions/reflections, as needed; changing the metaphors to be culturally congruent; and modifying content to make it responsive to Latino cultural values and norms. Conclusions: Findings demonstrate the need for adaptation to achieve the aims of the intervention, accounting for both linguistic and cultural considerations, emphasizing issues related to literacy, cultural and linguistic diversity, cultural values, and culturally congruent content. The mixed-methods approach is described to provide recommendations for clinicians, researchers, and program developers.