The effects of a prior malignancy on the survival of patients with ovarian cancer: a population-based study

Prognostic effects of previous cancer history on patients with major salivary gland cancer

OBJECTIVES

To explore the prognostic effects of previous cancer history on patients with major salivary gland cancer (SGC).

SUBJECTS AND METHODS

SGC patients with (sec-SGC) and without (one-SGC) a previous cancer from the SEER database were identified. Cox proportional hazards regression (CoxPH) models were used to compare the prognosis between sec-SGC and one-SGC patients. Subgroup analyses for sec-SGC patients by gender, previous cancer types, previous cancer histology, and cancer diagnosis interval (CDI) were performed. Two CoxPH models were constructed to distinguish sec-SGC patients with different prognostic risks.

RESULTS

9098 SGC patients were enrolled. Overall, sec-SGC patients (adjusted HR [aHR] = 1.26, p < 0.001), especially those with a CDI ≤ 5 years (aHR = 1.47, p < 0.001), had worse overall survival (OS) than one-SGC patients. In subgroup analysis, only sec-SGC patients with a previous head and neck cancer who were female (aHR = 2.38, p = 0.005), with a CDI ≤ 5 years (aHR = 1.65, p = 0.007) or with a previous squamous cell carcinoma (aHR = 6.52, p < 0.001) had worse OS. Our models successfully differentiated all sec-SGC patients into high-, intermediate- and low-risk groups with different prognosis.

CONCLUSIONS

Sec-SGC patients with different previous cancer types, gender, CDI and previous cancer histology had varied prognosis. The models we constructed could help differentiate the prognosis of sec-SGC patients with different risks.

Survival rate of ovarian cancer in Asian countries: a systematic review and meta-analysis

BACKGROUND

Ovarian cancer is amongst one of the most commonly occurring cancers affecting women, and the leading cause of gynecologic related cancer death. Its poor prognosis and high mortality rates can be attributed to the absence of specific signs and symptoms until advance stages, which frequently leads to late diagnosis. Survival rate of patients diagnosed with ovarian cancer can be used in order to better assess current standard of care; the aim of this study is to evaluate the survival rate of ovarian cancer patients in Asia.

METHODS

Systematic review was performed on articles that were published by the end of August 2021 in five international databases, including Medline / PubMed, ProQuest, Scopus, Web of Knowledge, and Google Scholar. The Newcastle-Ottawa quality evaluation form was used for cohort studies to evaluate the quality of the articles. The Cochran-Q and I² tests were used to calculate the heterogeneity of the studies. The Meta-regression analysis was also done according to when the study was published.

RESULTS

A total of 667 articles were reviewed, from which 108 were included in this study because they passed the criteria. Based on a randomized model, the survival rates of ovarian cancer after 1, 3 and 5 years were respectively 73.65% (95% CI, 68.66-78.64), 61.31% (95% CI, 55.39-67.23) and 59.60% (95% CI, 56.06-63.13). Additionally, based on meta-regression analysis, there was no relationship between the year of study and survival rate.

CONCLUSIONS

The 1-year survival rate was higher than that of 3- and 5-year for ovarian cancer. This study provides invaluable information that can not only help establish better standard of care for treatment of ovarian cancer, but also assist in development of superior health interventions for prevention and treatment of the disease.

Understanding common key indicators of successful and unsuccessful cancer drug trials using a contrast mining framework on ClinicalTrials.gov

Clinical trials are essential to the process of new drug development. As clinical trials involve significant investments of time and money, it is crucial for trial designers to carefully investigate trial settings prior to designing a trial. Utilizing trial documents from ClinicalTrials.gov, we aim to understand the common characteristics of successful and unsuccessful cancer drug trials to provide insights about what to learn and what to avoid. In this research, we first computationally classified cancer drug trials into successful and unsuccessful cases and then utilized natural language processing to extract eligibility criteria information from the trial documents. To provide explainable and potentially modifiable recommendations for new trial design, contrast mining was applied to discoverhighly contrasted patterns with a significant difference in prevalence between successful (completion with advancement to the next phase) and unsuccessful (suspended, withdrawn, or terminated) groups. Our method identified contrast patterns consisting of combinations of drug categories, eligibility criteria, study organization, and study design for nine major cancers. In addition to a literature review for the qualitative validation of mined contrast patterns, we found that contrast-pattern-based classifiers using the top 200 contrast patterns as feature representations can achieve approximately 80% F₁ score for eight out of ten cancer types in our experiments. In summary, aligning with the modernization efforts of ClinicalTrials.gov, our study demonstrates that understanding the contrast characteristics of successful and unsuccessful cancer trials may provide insights into the decision-making process for trial investigators and therefore facilitate improved cancer drug trial design.

Effect of prior thyroid cancer on survival of primary liver cancer: a study based on the SEER database

To explore the effect of prior thyroid cancer on the survival of primary liver cancer (PLC). Eligible PLC patients were selected from the Surveillance, Epidemiology, and End Results (SEER) database during 2004-2016. Propensity score matching (PSM) was used to create a highly comparable control group that PLC patients without prior thyroid cancer. All PLC patients were divided into three groups based on the survival information: (1) PLC-specific death; (2) death due to other causes; (3) alive. The effect sizes were presented by the corresponding hazard ratio (HR) and 95% confidence intervals (CI). Totally, 142 PLC patients with prior thyroid cancer and 1420 PLC patients without prior thyroid cancer were included. During the follow-up period, 714 (45.71%) PLC patients died of liver cancer while 638 (40.85%) PLC patients were alive. Median survival time for PLC patients was 11.00 months, respectively. PLC patients with prior thyroid cancer have a lower risk of death (HR = 0.64; 95% CI: 0.48-0.86). Subgroup analyses stratified by gender displayed the similar relation in female patients with PLC. Prior thyroid cancer may be a protective factor for liver cancer death in PLC patients, especially in female patients.

Primary ovarian cancer after colorectal cancer: a Dutch nationwide population-based study

BACKGROUND AND PURPOSE

Women with colorectal cancer (CRC) are at risk not only of developing ovarian metastases, but also of developing a primary ovarian malignancy. Several earlier studies have in fact shown a link between the development of primary ovarian cancer and CRC. The purpose of this study was therefore to determine the risk of developing a primary ovarian cancer in women with prior CRC compared to the general population.

METHODS

Data from the Netherlands Cancer Registry were used. All women diagnosed with invasive CRC between 1989 and 2017 were included. Standardized incidence ratios (SIRs) and absolute excess risks (AERs) per 10,000 person-years were calculated.

RESULTS

During the study period, 410 (0.3%) CRC patients were diagnosed with primary ovarian cancer. Women with CRC had a 20% increased risk of developing ovarian cancer compared to the general population (SIR = 1.2, 95% CI: 1.1-1.3). The AER of ovarian cancer was 0.9 per 10,000 person-years. The risk was especially increased within the first year of a CRC diagnosis (SIR = 3.3, 95% CI: 2.8-3.8) and in women aged ≤ 55 years (SIR = 2.0, 95% CI: 1.6-2.6).

CONCLUSION

This study found a slightly increased risk of primary ovarian cancer in women diagnosed with CRC compared to the general population. However, this may be partly attributable to surveillance or detection bias. Nevertheless, our findings could be helpful for patient counseling, as CRC patients do not currently receive information concerning the increased risk of ovarian cancer.

Risk and prognosis of second primary cancers among ovarian cancer patients, based on SEER database

The purposes of the present study were to elucidate the risk and prognostic effect of second primary cancers (SPCs) development, as well as the factors influencing the prognosis of OC patients with SPCs. A statistically significant increase in SPCs risk was observed among OC patients during 2004-2015. The independent factors were used to construct the SPCs-prediction nomogram and the OS-prediction nomogram. Both nomogram were subjected to internal validation and performed well. OC patients with SPCs have a better prognosis than patients without SPCs. Propensity score matching (PSM) was applied to reduce confounding.

Better Prognosis and Survival in Esophageal Cancer Survivors After Comorbid Second Primary Malignancies: A SEER Database-Based Study

Background

With the development of surgical techniques and advances in systemic treatments, the survival time of esophageal cancer survivors has increased; however, the chance of developing a second primary malignancy (SPM) has also increased. These patients’ prognosis and treatment plans remain inconclusive.

Objectives

We aimed to evaluate and predict the survival of patients with esophageal cancer with second primary tumors, to provide insights and the latest data on whether to pursue more aggressive treatment.

Materials and Methods

We selected esophageal cancer cases from the latest available data from the SEER database on April 15, 2021. We performed life table analysis, Kaplan–Meier analysis, and univariate and multivariate Cox proportional hazards analysis to assess the patient data. We conducted multiple Cox regression equation analyses under multiple covariate adjustment models, and performed a stratified analysis of multiple Cox regression equation analysis based on different covariates. To describe our study population more simply and clearly, we defined the group of patients with esophageal cancer combined with a second primary malignant tumor (the first of two or more primaries) as the EC-SPM group.

Results

Our analysis of 73,456 patients with esophageal cancer found the median survival time of the EC-SPM group was 47.00 months (95% confidence interval (CI), 43.87–50.13), and the mean survival time was 74.67 months (95% CI, 72.12–77.22). Kaplan–Meier curves of different esophageal cancer survivors showed that the survival of the EC-SPM group was significantly better than that of the other groups (p < 0.01). Univariate Cox regression analysis showed that compared with only one malignancy only group, the hazard ratio (HR) of the EC-SPM group was 0.95 (95% CI, 0.92–0.99; p < 0.05). In the multivariate Cox regression analysis under different adjustment models, the EC-SPM group had a reduced risk of death compared with the one primary malignancy only group (HR < 1, p < 0.05).

Conclusion

Survivors of esophageal cancer with a second primary malignant cancer have a better prognosis, but require more aggressive treatment. This study provided new evidence and new ideas for future research on the pathophysiological mechanism and treatment concepts of esophageal cancer combined with SPM.

Trends in the proportion of second or later primaries among all newly diagnosed malignant cancers

BACKGROUND

Improvements in cancer survival mean that an increasing number of survivors may live long enough beyond their initial cancer to be diagnosed with additional independent primary cancers. The proportion of newly diagnosed cancers that are second- or higher-order primaries and how this proportion has changed over the past several decades were examined.

METHODS

Data from the Surveillance, Epidemiology, and End Results (SEER) program were used to identify incident malignant primaries diagnosed between 1975 and 2017. Using the SEER sequence number, the authors tabulated the proportion of all cancers in each calendar year that were second- or higher-order primaries. The average annual percent change (AAPC) was then calculated to assess how this proportion has changed over time.

RESULTS

Analyses included nearly 4.9 million incident cancers diagnosed during 1975-2017. The proportion of all cancers that were second- or higher-order increased steadily from 9.77% during 1975-1984 to 21.03% during 2015-2017, reflecting an AAPC of 2.41% (95% CI, 2.16%-2.65%). In 2015-2017, second- or higher-order cancers were most prevalent among cancers of the bladder (28.79%), followed by lung and bronchus (28.07%), melanoma (27.88%), and leukemia (26.10%). The highest AAPCs over the study period were observed for melanoma (4.05%), leukemia (3.51%), and lung and bronchus (3.36%).

CONCLUSIONS

The proportion of newly diagnosed cancers that are second- or higher-order has grown rapidly over the past several decades and currently exceeds 20%. Continued monitoring of second and later primaries will be critical for anticipating the future impact on cancer treatment and survivorship care.