Age-specific survival in prostate cancer using machine learning

2020 ◽  
Vol 54 (2) ◽  
pp. 215-234
Author(s):  
M.N. Doja ◽  
Ishleen Kaur ◽  
Tanvir Ahmad
Keyword(s):  
Prostate Cancer ◽  
Machine Learning ◽  
Metastatic Prostate Cancer ◽  
Information Gain ◽  
Age Groups ◽  
Weighted Average ◽  
Age Group ◽  
Content Type ◽  
Complete Dataset ◽  
Average Accuracy

PurposeThe incidence of prostate cancer is increasing from the past few decades. Various studies have tried to determine the survival of patients, but metastatic prostate cancer is still not extensively explored. The survival rate of metastatic prostate cancer is very less compared to the earlier stages. The study aims to investigate the survivability of metastatic prostate cancer based on the age group to which a patient belongs, and the difference between the significance of the attributes for different age groups.Design/methodology/approachData of metastatic prostate cancer patients was collected from a cancer hospital in India. Two predictive models were built for the analysis-one for the complete dataset, and the other for separate age groups. Machine learning was applied to both the models and their accuracies were compared for the analysis. Also, information gain for each model has been evaluated to determine the significant predictors for each age group.FindingsThe ensemble approach gave the best results of 81.4% for the complete dataset, and thus was used for the age-specific models. The results concluded that the age-specific model had the direct average accuracy of 83.74% and weighted average accuracy of 79.9%, with the highest accuracy levels for age less than 60.Originality/valueThe study developed a model that predicts the survival of metastatic prostate cancer based on age. The study will be able to assist the clinicians in determining the best course of treatment for each patient based on ECOG, age and comorbidities.

Docetaxel in older patients for metastatic prostate cancer.

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 187-187 ◽  
Author(s):  
Frances May Mark ◽  
Adam Pollard ◽  
Alastair H Thomson
Keyword(s):  
Prostate Cancer ◽  
Overall Survival ◽  
Clinical Practice ◽  
Metastatic Prostate Cancer ◽  
Age Groups ◽  
Response Rates ◽  
Routine Clinical Practice ◽  
Age Group ◽  
Psa Response ◽  
Castrate Resistant

187 Background: Docetaxel use has led to a significant prolongation in overall survival in metastatic prostate cancer (MPC). There is however limited information on treatment tolerance and outcomes in patients 80 years old and over in routine clinical practice. With the ever aging population it is becoming more important to assess outcomes in this age group. Methods: Patients diagnosed with MPC and treated with docetaxel from 2006 to 2016 were identified and their records retrospectively reviewed via electronic clinical and prescribing systems in a single centre in the UK. Data was assessed for prostate specific antigen (PSA) response, number of cycles and dosing of docetaxel and castrate resistant overall survival (OS). Results: 209 consecutive patients with MPC receiving docetaxel were reviewed. Three patient groups were identified; younger than 75 years old (n = 150, 37 early (as part of initial therapy) docetaxel), 75-79 years (n = 40, 2 early docetaxel) and 80 years or over (n = 19, no early docetaxel). When comparing mean OS excluding early docetaxel treatment, respective mean survival times for each of the three age groups, younger to older were 1001, 1045 and 1294 days, with between class difference being insignificant. The PSA response rates to docetaxel excluding first line use were compared between the age groups and did not show a significant difference at 39% in the youngest group, 38% in the intermediate age group and 42% for the oldest patients. There was a trend that the older the patient, the more likely docetaxel was the final systemic treatment given at 42% (80 years or over), 32% (75-79 years) and 23% (younger than 75 years). The 80 years or over group received fewer docetaxel cycles (3.8, p = 0.006) and less dose per course (226mg/m2, p = 0.004) than the group less than 75 years (5.8 cycles, 409mg/m2) and 75-79 years (5.1 cycles, 341mg/m2). Conclusions: In this group of patients, in routine clinical practice, the 80 years and over age group received fewer cycles of docetaxel in MPC and less dose per course, but nevertheless achieved similar PSA response rates and castrate resistant OS. Given these results, docetaxel should be considered as a treatment option in suitable patients of 80 years and over.

Age and outcome after aneurysmal subarachnoid hemorrhage: why do older patients fare worse?

1996 ◽  
Vol 85 (3) ◽  
pp. 410-418 ◽  
Author(s):  
Giuseppe Lanzino ◽  
Neal F. Kassell ◽  
Teresa P. Germanson ◽  
Gail L. Kongable ◽  
Laura L. Truskowski ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Subarachnoid Hemorrhage ◽  
Age Groups ◽  
Age Group ◽  
Content Type ◽  
Poor Outcome ◽  
Symptomatic Vasospasm ◽  
Age Related ◽  
Increased Risk ◽  
Fine Print

✓ Advanced age is a recognized prognostic indicator of poor outcome after subarachnoid hemorrhage (SAH). The relationship of age to other prognostic factors and outcome was evaluated using data from the multicenter randomized trial of nicardipine in SAH conducted in 21 neurosurgical centers in North America. Among the 906 patients who were studied, five different age groups were considered: 40 years or less, 41 to 50, 51 to 60, 61 to 70, and more than 71 years. Twenty-three percent of the individuals enrolled were older than 60 years of age. Women outnumbered men in all age groups. Level of consciousness (p = 0.0002) and World Federation of Neurological Surgeons grade (p = 0.0001) at admission worsened with advancing age. Age was also related to the presence of a thick subarachnoid clot (p = 0.0001), intraventricular hemorrhage (p = 0.0003), and hydrocephalus (p = 0.0001) on an admission computerized tomography scan. The rebleeding rate increased from 4.5% in the youngest age group to 16.4% in patients more than 70 years of age (p = 0.002). As expected, preexisting medical conditions, such as diabetes (p = 0.028), hypertension (p = 0.0001), and pulmonary (p = 0.0084), myocardial (p = 0.0001), and cerebrovascular diseases (p = 0.0001), were positively associated with age. There were no age-related differences in the day of admission following SAH, timing of the surgery and/or location, and size (small vs. large) of the ruptured aneurysm. During the treatment period, the incidence of severe complications (that is, those complications considered life threatening by the reporting investigator) increased with advancing age, occurring in 28%, 33%, 36%, 40%, and 46% of the patients in each advancing age group, respectively (p = 0.0002). No differences were observed in the reported frequency of surgical complications. No age-related differences were found in the overall incidence of angiographic vasospasm; however, symptomatic vasospasm was more frequently reported in the older age groups (p = 0.01). Overall outcome, assessed using the Glasgow Outcome Scale at 3 months post-SAH, was poorer with advancing age (p < 0.001). Multivariate analysis of overall outcome, adjusting for the different prognostic factors, did not remove the age effect, which suggests that the aging brain has a less optimal response to the initial bleeding. Age as a risk factor is a continuum; however, there seems to be a significant increased risk of poor outcome after the age of 60 years.

Quality of life in young men after radical prostatectomy: Results from the CaPSURE registry

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 4576-4576 ◽  
Author(s):  
J. L. Wright ◽  
D. W. Lin ◽  
J. E. Cowan ◽  
J. Duchane ◽  
P. R. Carroll ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Prostate Cancer ◽  
Radical Prostatectomy ◽  
Age Groups ◽  
Older Men ◽  
Multivariate Model ◽  
Age Group ◽  
Younger Men ◽  
One Year

4576 Background: Over the past two decades, the age at diagnosis and treatment of men with prostate cancer (CaP) has steadily declined. Previous work suggests that younger men have similar or improved pathologic and clinical outcomes compared to older men. The literature on quality of life (QOL) following local treatment for CaP has primarily focused on comparing treatment modalities rather than specific age groups. This analysis explored QOL outcomes in younger men following primary curative treatment for localized prostate cancer. Methods: This was a secondary analysis of a prospectively collected cohort from the CaPSURE (Cancer of the Prostate Strategic Urologic Endeavor) registry. Men who underwent radical prostatectomy (RP) for localized disease and completed the UCLA Prostate Cancer Index (PCI) pre- and one-year post-surgery were identified. Men were grouped based on age (< 55, 55–64, ≥ 65 years). A severe decline in PCI domains from pre- to post-RP was defined as a decrease of one standard deviation from the pre-RP score. PCI scores were compared across age groups, and a multivariate model created to analyze the predictors of severe declines in PCI domains. Results: 1,143 men were identified, with 190, 526 and 427 men in the three age groups, respectively. Younger men had significantly higher mean scores one-year after RP in the urinary function (UF), urinary bother (UB) and sexual function (SF) domains of the PCI. The proportion of men with a severe decline in UF, UB and SF was not significantly different in the age groups (range 49–54%, 32–38%, 58–51% respectively). However, a severe decline in SB was more common in the youngest age group than in the oldest (54% vs. 36%, p < 0.01). With the youngest men as the reference group in the multivariate model, the oldest age group was 40% less likely to have a severe decline of SB (OR = 0.60, 95% CI 0.41–0.90, p = 0.04) but trended toward a higher risk of severe decline in UB (OR = 1.27, 95% CI 0.85–1.89, p = 0.08). Conclusions: Age predicts disease-specific QOL changes at one-year following RP. Younger men had significantly better mean UF, UB, and SF domain scores one-year after RP than did their older counterparts. Men < 55 years old are more likely than older men to experience a severe decline of sexual bother but trend toward a lower risk of a severe urinary bother. No significant financial relationships to disclose.

The changing face of cancer in the elderly—Only a demographic change?

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 18597-18597
Author(s):  
Y. Rottenberg ◽  
T. Peretz
Keyword(s):  
Breast Cancer ◽  
Prostate Cancer ◽  
Lung Cancer ◽  
Older Women ◽  
Age Groups ◽  
The Elderly ◽  
Age Group ◽  
Industrial Countries ◽  
Cancer Burden ◽  
Two Age Groups

18597 Background: In industrial countries, the cancer burden of the elderly is high and is increased. One reason is longer life expectancy. Increasing age standardized rates of cancer in this age group compared to younger groups may also explain this phenomenon. Methods: Two age groups were examined, above and below 65 years. Each age group was further divided into men and women. The age standardized rates for all cancers combined among the Jewish population in Israel were identified through the Israel Cancer Registry during the years 1973–2002. In addition, lung and colorectal cancers according to sexes, prostate cancer in men and breast cancer in women were examined. Results: Between the first 5 years of the study (1973–1977) and the last 5 years (1998–2002) the age standardized rates for all cancers combined were raised by about one third in the two age groups. In males, the overall change was higher in the older group (42% in men aged 65 years and older compared to 31% in men younger than 65). However, the rise in the younger group was more prominent in females (42% in women younger than 65 years compared to 33 % in women aged 65 and older). The most outstanding increase was in prostate cancer in men, but mainly in the younger group (176% in the older group and 368% in the younger group) followed by breast cancer in women, more prominent in the older group (64% in the older group and 50% in the younger group). In both sexes, more noticeable increases were noted in the older groups in colorectal cancer and in lung cancer. Between the years 1993–1997 and 1998–2002 shifts towards stabilization and even a decrease was noted in some of the cancers that were examined. In men aged 65 years and older rates for all cancers combined were decreased by 2.5%, among the specific tumors and a decrease was noted in lung cancer (6.7%) and prostate cancer (5.8%). The rates for all cancers combined among the older women were slightly decreasing (2.0%). No decrease was noted in the specific tumors in this group. Among the younger groups in both sexes, no decrease (defined >0.5%) was noted. Conclusions: These data argue against the hypothesis that the overall change in the cancer burden in the aged could be also explained by differences changes in the risk of developing cancer between these two age groups. No significant financial relationships to disclose.

scholarly journals Predicting Age Groups of Reddit Users Based on Posting Behavior and Metadata: Classification Model Development and Validation (Preprint)

2020 ◽  
Author(s):  
Robert Chew ◽  
Caroline Kery ◽  
Laura Baum ◽  
Thomas Bukowski ◽  
Annice Kim ◽  
...  
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Social Media ◽  
Age Groups ◽  
Demographic Characteristics ◽  
Machine Learning Algorithms ◽  
Classification Model ◽  
Age Group ◽  
Adult Group ◽  
Linguistic Patterns

BACKGROUND Social media are important for monitoring perceptions of public health issues and for educating target audiences about health; however, limited information about the demographics of social media users makes it challenging to identify conversations among target audiences and limits how well social media can be used for public health surveillance and education outreach efforts. Certain social media platforms provide demographic information on followers of a user account, if given, but they are not always disclosed, and researchers have developed machine learning algorithms to predict social media users’ demographic characteristics, mainly for Twitter. To date, there has been limited research on predicting the demographic characteristics of Reddit users. OBJECTIVE We aimed to develop a machine learning algorithm that predicts the age segment of Reddit users, as either adolescents or adults, based on publicly available data. METHODS This study was conducted between January and September 2020 using publicly available Reddit posts as input data. We manually labeled Reddit users’ age by identifying and reviewing public posts in which Reddit users self-reported their age. We then collected sample posts, comments, and metadata for the labeled user accounts and created variables to capture linguistic patterns, posting behavior, and account details that would distinguish the adolescent age group (aged 13 to 20 years) from the adult age group (aged 21 to 54 years). We split the data into training (n=1660) and test sets (n=415) and performed 5-fold cross validation on the training set to select hyperparameters and perform feature selection. We ran multiple classification algorithms and tested the performance of the models (precision, recall, F1 score) in predicting the age segments of the users in the labeled data. To evaluate associations between each feature and the outcome, we calculated means and confidence intervals and compared the two age groups, with 2-sample t tests, for each transformed model feature. RESULTS The gradient boosted trees classifier performed the best, with an F1 score of 0.78. The test set precision and recall scores were 0.79 and 0.89, respectively, for the adolescent group (n=254) and 0.78 and 0.63, respectively, for the adult group (n=161). The most important feature in the model was the number of sentences per comment (permutation score: mean 0.100, SD 0.004). Members of the adolescent age group tended to have created accounts more recently, have higher proportions of submissions and comments in the r/teenagers subreddit, and post more in subreddits with higher subscriber counts than those in the adult group. CONCLUSIONS We created a Reddit age prediction algorithm with competitive accuracy using publicly available data, suggesting machine learning methods can help public health agencies identify age-related target audiences on Reddit. Our results also suggest that there are characteristics of Reddit users’ posting behavior, linguistic patterns, and account features that distinguish adolescents from adults.

From children to seniors: is culture accessible to everyone?

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aleksandra Tešin ◽  
Sanja Kovačić ◽  
Tatjana Pivac ◽  
Miroslav D. Vujičić ◽  
Sanja Obradović
Keyword(s):  
Statistical Analysis ◽  
Design Methodology ◽  
Age Groups ◽  
Age Group ◽  
Cultural Institutions ◽  
Online Questionnaire ◽  
Content Type ◽  
Novi Sad ◽  
The City ◽  
Descriptive Statistical Analysis

Purpose The main objective of the study is to analyse the perception of accessibility to cultural for different age groups (children, teenagers, adults and seniors) in the city of Novi Sad (Serbia). Additional goals were to reveal which cultural contents in the city are the most important to which particular age group and to measure the level of compatibility with their needs. Design/methodology/approach The study sample consisted of 170 respondents of different age groups used for comparison purposes. Data were collected through an online questionnaire and analysed by IBM SPSS Statistics (descriptive statistical analysis and ANOVA test). Findings The results of this research showed that a gap is evident between the current cultural offer and the needs and preferences of visitors of different age groups. One of the significant obstacles that emerged is the inadequate promotion of cultural contents in the city to different age groups of visitors (children, teenagers, adults and seniors). The study also identified the age groups of visitors to whom the cultural offer was least adapted, as well as mapping the cultural institutions which are least accessible to audiences of different ages. Originality/value The paper addresses the knowledge gap related to accessibility to cultural for different generations. It focuses on topics that have not been previously researched – comparison of the needs of different generations concerning the actual offer in cultural institutions, addressing the importance of certain elements of a cultural offer to different age groups and the level of accessibility of such features to different age groups.

scholarly journals Influence of Baseline Cardiovascular Comorbidities on Mortality after Androgen Deprivation Therapy for Metastatic Prostate Cancer

Cancers ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 189
Author(s):  
Szu-Yuan Wu ◽  
Su-Chen Fang ◽  
Olivia Rachel Hwang ◽  
Hung-Jen Shih ◽  
Yu-Hsuan Joni Shao
Keyword(s):  
Prostate Cancer ◽  
Androgen Deprivation Therapy ◽  
Survival Benefit ◽  
Metastatic Prostate Cancer ◽  
Cox Model ◽  
Age Groups ◽  
Androgen Deprivation ◽  
Cardiovascular Comorbidities ◽  
Specific Mortality ◽  
The Status

Few studies have assessed the benefits of androgen deprivation therapy (ADT) in men with metastatic prostate cancer (PC; mPC) at an old age or with major cardiovascular conditions. A retrospective cohort consisted of 3835 men with newly diagnosed mPC from the Taiwan Cancer Registry of 2008–2014. Among them, 2692 patients received only ADT in the first year after the cancer diagnosis, and 1143 patients were on watchful waiting. The inverse probability of treatment-weighted Cox model was used to estimate the effects of ADT on all-cause mortality and PC-specific mortality according to age, and the status of congestive heart failure (CHF), coronary arterial diseases (CADs), and stroke at the baseline. After a median follow-up of 2.65 years, 1650 men had died. ADT was associated with a 17–22% risk reduction in all-cause and PC-specific mortality in men without stroke, CAD, or CHF in the 65–79-year group. The survival benefit diminished in men with any of these preexisting conditions. In contrast, ADT was not found to be associated with any survival benefit in the ≥80-year group, even though they did not present with any major cardiovascular disease at the baseline. Patients who had CHF, CAD, or stroke at the baseline did not show a survival benefit following ADT in any of the age groups. Men who have preexisting major cardiovascular diseases or are ≥80 years do not demonstrate a survival benefit from ADT for mPC. The risk–benefit ratio should be considered when using ADT for mPC in older men especially those with major cardiovascular comorbidities.

scholarly journals Screening for Prostate Cancer by Digital Rectal Examination and PSA Determination in Senegal

ISRN Oncology ◽  
2011 ◽  
Vol 2011 ◽  
pp. 1-4 ◽  
Author(s):  
Lamine Niang ◽  
Charles N. Kouka ◽  
Mohamed Jalloh ◽  
Sérigne M. Gueye
Keyword(s):  
Prostate Cancer ◽  
Positive Predictive Value ◽  
Predictive Value ◽  
Age Groups ◽  
Digital Rectal Examination ◽  
Data Entry ◽  
Age Group ◽  
Rectal Examination ◽  
Prostate Biopsies ◽  
Unselected Population

Objectives. The goal of our study was to investigate the prevalence of prostate cancer in an unselected population of Senegalese men. Patients and Methods. We conducted the study over two years (2008 and 2009) on an unselected population of 572 Senegalese men, aged 35 and older. The following parameters have been investigated: the subject's age, the presence or absence of urination disorders, the family's history of prostate cancer or prostate surgery, the aspects of the prostate on digital rectal examination (DRE), the total PSA level, and the outcomes of the prostate biopsies. Data entry was performed with Epi Info 6 software and was analyzed and recorded using Excel software. We performed mean and frequency calculations. Results. The mean age of our patients was 65.5 years, with extremes of 38 and 93 years. Age groups from 50 to 59 and from 60 to 69 were the most represented. DRE was normal in the age group from 35 to 39, and only one patient in the age group from 40 to 49 had a prostate nodule. PSA level was greater than or equal to 4 ng/mL in 66 cases. A total of 5.4% patients had a PSA level greater than or equal to 10 ng/mL. Only two patients in the age group from 40 to 49 had a PSA level greater than 4 ng/mL. Of the 72 biopsies we performed, prostatic adenocarcinoma was found in 30.6% of the cases. It is the only type of prostate cancer we found in our series. The cases of prostate cancer were mostly observed in the age groups from 60 to 69 and from 70 to 79. No cases were detected for ages younger than 50. DRE gave indications of possible adenocarcinoma in 27.30% cases. Its sensitivity was 27%, while its positive predictive value was estimated at 35%. Of all positive biopsies, 4.5% had a PSA level between 0 and 3.9 ng/mL. In this case, the sensitivity of PSA was 95.5%, and the positive predictive value was 31.8%. High-grade intraepithelial neoplasiae were observed in 21 cases. Conclusion. Prostate cancer is frequent in Senegal, and screening remains the best way for early diagnosis.

scholarly journals Establish a predictive model for high-risk de novo metastatic prostate cancer patients by machine learning.

2019 ◽  
Vol 5 (suppl) ◽  
pp. 13-13
Author(s):  
Po-Jung SU ◽  
Yu-Ann Fang ◽  
Yung-Chun Chang ◽  
Yung-Chia Kuo ◽  
Yung-Chang Lin
Keyword(s):  
Prostate Cancer ◽  
Machine Learning ◽  
High Risk ◽  
Cancer Patients ◽  
Metastatic Prostate Cancer ◽  
De Novo ◽  
Risk Group ◽  
High Risk Group ◽  
Recursive Feature Elimination ◽  
Risk Patients

13 Background: For de novo metastatic prostate cancer (mPC)) patients, their prognosis may be really different. Some of these patients response very well to hormone therapy with durable survival, but others may be not. For those poor prognosis patients, if we could predict them as high risk patients when diagnosed, and provide aggressive upfront chemotherapy or novel hormonal therapy, they might get better treatment outcomes. Methods: We used data of prostate cancer patients from 2000 to 2016 in Chang Gung Research Database. There are 799 de novo mPC patients with castration. We predicted the possibility for these patients progressed to metastatic castration-resistant prostate cancer (mCRPC) in 1 year and find the high risk group patients. Then we figured out the best features for prediction from the best classifier with Recursive Feature Elimination. Results: The de nove mPC patients who pregressed to mCRPC in 1 year, whose mOS is 21.9 months is worse than who progressed to mCRPC beyond 1 year significantly, whose mOS is 80.7 months. (adjusted hazard ratio[aHR]: 6.43, P<0.001). The overall performance of machine learning by XGBoost is the best in all predictive models for high risk patients. (AUC=0.7000, Accuracy=0.7143). We excluded the features with missing data over 50%, then put all other features in the model. (AUC=0.7042, Accuracy=0.7239). But we got the best performance with only 11 features, including age, time from diagnosis to castration, nadir PSA, hemoglobin, eosinophil/white blood cell ratio, alkaline phosphatase, alanine transaminase, blood urea nitrogen, creatinine, prothrombin time, and secondary primary cancer, by Recursive Feature Elimination. (AUC=0.7131, Accuracy=0.7267). Conclusions: We found the predictive model has better predictive accuracy and shorter manuscript time with less features selected by Recursive Feature Elimination.We can predict high risk group in de novo mPC patients and make better clinical decision for treatment with this XGBoost model.

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