version 0.1.0

DESCRIPTION

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+Package: metaSurvival
+Type: Package
+Title: Meta-Analysis of a Single Survival Curve
+Version: 0.1.0
+Date: 2020-12-04
+Authors@R: person(given = "Shubhram", 
+                  family ="Pandey", 
+                  email = "shubhram1992@gmail.com",
+                  role = c("aut", "cre"))
+Maintainer: Shubhram Pandey <shubhram1992@gmail.com>
+Description: To assess a summary survival curve from survival probabilities and number of at-risk patients collected at various points in time in various studies, and to test the between-strata heterogeneity.
+License: MIT + file LICENSE
+Encoding: UTF-8
+LazyData: true
+Imports: mvtnorm, survival
+RoxygenNote: 7.1.1
+Depends: R (>= 2.10)
+Suggests: knitr, rmarkdown
+URL: https://github.com/shubhrampandey/metaSurvival
+BugReports: https://github.com/shubhrampandey/metaSurvival/issues
+NeedsCompilation: no
+Packaged: 2020-12-04 16:32:32 UTC; PandeyS6
+Author: Shubhram Pandey [aut, cre]
+Repository: CRAN
+Date/Publication: 2020-12-07 10:20:02 UTC

LICENSE

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+YEAR: 2020
+COPYRIGHT HOLDER: Shubhram Pandey

MD5

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+f764be5533597ab07406067995ef733f *DESCRIPTION
+82b9d4c1732fb89795c5d768191a8565 *LICENSE
+9a527e481156dbe3950ed822a983dfc7 *NAMESPACE
+25100d5991a5c1814fe43148a45d776a *NEWS.md
+61abb940ba99fb792d443487415a1821 *R/exampleData.R
+7a8396baccd2e68558f21247cb0455cb *R/msurv.R
+ef1d1da38a42fa5c60abc4c8505f3682 *README.md
+dca78834e0c974111fec324784efd20d *data/exampleData.rda
+f7fa0daffb3e139e53cc653fd7a59814 *man/exampleData.Rd
+502a5f8dd6ba90060101596366cb7d58 *man/figures/README-pressure-1.png
+9820650b8015b27ceccb69bbd490ac0a *man/figures/README-unnamed-chunk-4-1.png
+3508259bc473cf8f47210480377d976d *man/figures/README-unnamed-chunk-6-1.png
+825ab56c717c3e836ca194b53b572c45 *man/msurv.Rd

NAMESPACE

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+# Generated by roxygen2: do not edit by hand
+
+export(msurv)
+importFrom(stats,quantile)

NEWS.md

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+# metaSurvival 0.1.0
+
+* Added a `NEWS.md` file to track changes to the package.

R/exampleData.R

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+#' The data extracted from a meta-analysis by Cabibbo et al.
+#'
+#'Data were extracted from the studies included in the meta-analysis by Cabibbo et al. which aimed to assess the survival rate in untreated patients with hepatocellular carcinoma.
+#'
+#' @format A data frame with with the 8 following variables (columns).
+#' \describe{
+#'   \item{Study}{This numeric vector represents number of the study.}
+#'   \item{FirstAuthor}{This vector represents the name of the first author.}
+#'   \item{YearPub}{This numeric vector represents the publication year.}
+#'   \item{Time}{This numeric vector represents the times for which the survival rates are collected in years.}
+#'   \item{Survival}{This numeric vector represents the survival rates for each value of Time}
+#'   \item{NbRisk}{This numeric vector represents the number of at-risk patients for each value of Time}
+#'   \item{Location}{This factor indicates the location of the study (Asia, North Amercia or Europe)}
+#'   \item{Design}{This factor indicates if the study is monocentric ou multicentric.}
+#'   ...
+#' }
+#'
+#' @details The survival probabilities were extracted from the published survival curves each month during the first six months and then by step of three months. The pictures of the curves were digitalized using the R package ReadImage and the probabilities were extracted using the package digitize proposed by Poisot. The numbers of at-risk patients for each interval of time were derived from the numbers of at-risk patients reported in the studies, and using the methods of Parmar or Williamson to account for censorship. Studies have different length of follow-up. For each study, survival probabilities and the numbers of at-risk patients were collected at all points in time before the end of follow-up.
+#' @author Shubhram Pandey \email{shubhram.pandey@@PAREXEL.com}
+#'
+"exampleData"

README.md

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+
+<!-- README.md is generated from README.Rmd. Please edit that file -->
+
+# metaSurvival
+
+<!-- badges: start -->
+
+[![lifecycle](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental)
+[![License:
+MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)
+[![GitHub
+commit](https://img.shields.io/github/last-commit/shubhrampandey/metaSurvival)](https://github.com/shubhrampandey/metaSurvival/commit/master)
+[![Travis build
+status](https://travis-ci.com/shubhrampandey/metaSurvival.svg?branch=master)](https://travis-ci.com/shubhrampandey/metaSurvival)
+[![CRAN
+status](https://www.r-pkg.org/badges/version/metaSurvival)](https://CRAN.R-project.org/package=metaSurvival)
+<!-- badges: end -->
+
+The goal of metaSurvival is to …
+
+## Installation
+
+You can install the released version of metaSurvival from
+[CRAN](https://CRAN.R-project.org) with:
+
+``` r
+install.packages("metaSurvival")
+```
+
+And the development version from [GitHub](https://github.com/) with:
+
+``` r
+# install.packages("devtools")
+devtools::install_github("shubhrampandey/metaSurvival")
+```
+
+## Example
+
+``` r
+library(metaSurvival)
+```
+
+First start with loading the example dataset.
+
+``` r
+data(exampleData)
+attach(exampleData)
+head(exampleData)
+#>   Study FirstAuthor YearPub Time Survival NbRisk Location      Design
+#> 1     1         Lai    1988    1   0.8043     46     Asia Monocentric
+#> 2     1         Lai    1988    2   0.4565     37     Asia Monocentric
+#> 3     1         Lai    1988    3   0.2609     21     Asia Monocentric
+#> 4     1         Lai    1988    4   0.1739     12     Asia Monocentric
+#> 5     1         Lai    1988    5   0.1304      8     Asia Monocentric
+#> 6     1         Lai    1988    6   0.0870      6     Asia Monocentric
+```
+
+Computation of summary survival with continuity
+correction.
+
+``` r
+results<-msurv(Study, Time, NbRisk, Survival, confidence="Greenwood",correctionFlag = T,correctionVal = c(0.25,0.5))
+results
+#> $verif.data
+#>    Sstudy check
+#> 1       1     1
+#> 2       2     1
+#> 3       3     1
+#> 4       4     1
+#> 5       5     1
+#> 6       6     1
+#> 7       7     1
+#> 8       8     1
+#> 9       9     1
+#> 10     10     1
+#> 11     11     1
+#> 12     12     1
+#> 13     13     1
+#> 14     14     1
+#> 15     15     1
+#> 16     16     1
+#> 17     17     1
+#> 18     18     1
+#> 19     19     1
+#> 20     20     1
+#> 21     21     1
+#> 22     22     1
+#> 23     23     1
+#> 24     24     1
+#> 25     25     1
+#> 26     26     1
+#> 27     27     1
+#> 
+#> $summary.fixed
+#>       IndiceTimes PooledSurvivalFE PooledSurvivalICinfFE PooledSurvivalICsupFE
+#>  [1,]           1       0.94497450            0.93455418            0.95551100
+#>  [2,]           2       0.84347436            0.82683765            0.86044583
+#>  [3,]           3       0.73872717            0.71857893            0.75944035
+#>  [4,]           4       0.66245129            0.64073764            0.68490079
+#>  [5,]           5       0.58662304            0.56399133            0.61016291
+#>  [6,]           6       0.52144090            0.49844475            0.54549799
+#>  [7,]           9       0.40882896            0.38592475            0.43309252
+#>  [8,]          12       0.32461488            0.30222075            0.34866838
+#>  [9,]          15       0.26174091            0.23995379            0.28550624
+#> [10,]          18       0.21983127            0.19855264            0.24339029
+#> [11,]          21       0.18810271            0.16733508            0.21144777
+#> [12,]          24       0.16086195            0.14062988            0.18400476
+#> [13,]          27       0.13906070            0.11917994            0.16225783
+#> [14,]          30       0.12241028            0.10252475            0.14615276
+#> [15,]          33       0.09697105            0.07643349            0.12302702
+#> [16,]          36       0.08104941            0.06104672            0.10760623
+#> [17,]          39       0.07799121            0.05761503            0.10557365
+#> [18,]          42       0.06960868            0.04863084            0.09963571
+#> [19,]          45       0.06635655            0.04527093            0.09726311
+#> [20,]          48       0.06295069            0.04180072            0.09480195
+#> 
+#> $median.fixed
+#>              2.5%    97.5% 
+#> 6.571189 5.969119 7.163636 
+#> 
+#> $mean.fixed
+#>              2.5%    97.5% 
+#> 12.06584 11.28009 12.76527 
+#> 
+#> $heterogeneity
+#> [1] 731.217128   2.521438  60.340098
+#> 
+#> $summary.random
+#>       IndiceTimes PooledSurvivalRE PooledSurvivalICinfRE PooledSurvivalICsupRE
+#>  [1,]           1       0.93524921            0.90753843            0.96380610
+#>  [2,]           2       0.82628083            0.77535470            0.88055185
+#>  [3,]           3       0.70123428            0.63503595            0.77433335
+#>  [4,]           4       0.61766270            0.54632825            0.69831133
+#>  [5,]           5       0.53060766            0.45992592            0.61215181
+#>  [6,]           6       0.44916320            0.37511275            0.53783184
+#>  [7,]           9       0.32921715            0.26232834            0.41316134
+#>  [8,]          12       0.24431166            0.18426527            0.32392532
+#>  [9,]          15       0.18160515            0.13130502            0.25117417
+#> [10,]          18       0.14534074            0.10284269            0.20540041
+#> [11,]          21       0.11674507            0.07979975            0.17079517
+#> [12,]          24       0.09822802            0.06593733            0.14633204
+#> [13,]          27       0.08346181            0.05491511            0.12684802
+#> [14,]          30       0.07097460            0.04554526            0.11060193
+#> [15,]          33       0.05659698            0.03461920            0.09252720
+#> [16,]          36       0.04869511            0.02927924            0.08098617
+#> [17,]          39       0.04682745            0.02783640            0.07877493
+#> [18,]          42       0.03866701            0.02088712            0.07158177
+#> [19,]          45       0.03689963            0.01966964            0.06922256
+#> [20,]          48       0.03516081            0.01850465            0.06680927
+#> 
+#> $median.random
+#>              2.5%    97.5% 
+#> 5.375810 4.469860 6.676145 
+#> 
+#> $mean.random
+#>                2.5%     97.5% 
+#>  9.554813  7.764589 11.465606
+```
+
+Plot the estimates summary survival
+
+``` r
+RandomEffectSummary<- results$summary.random
+
+plot(Time, Survival, type="n", col="grey", ylim=c(0,1),xlab="Time",
+ ylab="Survival")
+
+for (i in unique(sort(Study))){
+lines(Time[Study==i], Survival[Study==i], type="l", col="grey")
+points(max(Time[Study==i]),
+ Survival[Study==i & Time==max(Time[Study==i])], pch=15)
+}
+
+lines(RandomEffectSummary[,1], RandomEffectSummary[,2], type="l",
+ col="red", lwd=3)
+points(RandomEffectSummary[,1], RandomEffectSummary[,3], type="l",
+ col="red", lty=3, lwd=3)
+points(RandomEffectSummary[,1], RandomEffectSummary[,4], type="l",
+ col="red", lty=3, lwd=3)
+```
+
+<img src="man/figures/README-unnamed-chunk-4-1.png" width="100%" />
+
+Computation of summary survival without continuity
+correction.
+
+``` r
+results<-msurv(Study, Time, NbRisk, Survival, confidence="Greenwood",correctionFlag = F)
+results
+#> $verif.data
+#>    Sstudy check
+#> 1       1     1
+#> 2       2     1
+#> 3       3     1
+#> 4       4     1
+#> 5       5     1
+#> 6       6     1
+#> 7       7     1
+#> 8       8     1
+#> 9       9     1
+#> 10     10     1
+#> 11     11     1
+#> 12     12     1
+#> 13     13     1
+#> 14     14     1
+#> 15     15     1
+#> 16     16     1
+#> 17     17     1
+#> 18     18     1
+#> 19     19     1
+#> 20     20     1
+#> 21     21     1
+#> 22     22     1
+#> 23     23     1
+#> 24     24     1
+#> 25     25     1
+#> 26     26     1
+#> 27     27     1
+#> 
+#> $summary.fixed
+#>       IndiceTimes PooledSurvivalFE PooledSurvivalICinfFE PooledSurvivalICsupFE
+#>  [1,]           1        0.9508837            0.93115618             0.9710293
+#>  [2,]           2        0.8542395            0.82202310             0.8877185
+#>  [3,]           3        0.7529489            0.71356234             0.7945096
+#>  [4,]           4        0.6801444            0.63752795             0.7256097
+#>  [5,]           5        0.6081467            0.56352148             0.6563058
+#>  [6,]           6        0.5449696            0.49936809             0.5947354
+#>  [7,]           9        0.4303415            0.38446782             0.4816886
+#>  [8,]          12        0.3452733            0.30011887             0.3972213
+#>  [9,]          15        0.2814425            0.23729653             0.3338012
+#> [10,]          18        0.2411057            0.19773211             0.2939935
+#> [11,]          21        0.2109529            0.16828161             0.2644443
+#> [12,]          24        0.1858428            0.14380950             0.2401619
+#> [13,]          27        0.1671095            0.12528742             0.2228921
+#> [14,]          30        0.1549979            0.11269730             0.2131760
+#> [15,]          33        0.1322367            0.08722757             0.2004703
+#> [16,]          36        0.1201395            0.07462625             0.1934106
+#> [17,]          39        0.1201395            0.07462625             0.1934106
+#> [18,]          42        0.1144864            0.06665886             0.1966300
+#> [19,]          45        0.1144864            0.06665886             0.1966300
+#> [20,]          48        0.1144864            0.06665886             0.1966300
+#> 
+#> $median.fixed
+#>              2.5%    97.5% 
+#> 7.176926 5.923614 8.344025 
+#> 
+#> $mean.fixed
+#>              2.5%    97.5% 
+#> 13.46370 11.45324 14.73451 
+#> 
+#> $heterogeneity
+#> [1] 219.6071244   0.7572659   0.0000000
+#> 
+#> $summary.random
+#>       IndiceTimes PooledSurvivalRE PooledSurvivalICinfRE PooledSurvivalICsupRE
+#>  [1,]           1       0.94768647            0.91731470             0.9790638
+#>  [2,]           2       0.84755282            0.78823478             0.9113348
+#>  [3,]           3       0.73182809            0.65606515             0.8163402
+#>  [4,]           4       0.65409564            0.56903170             0.7518757
+#>  [5,]           5       0.57872161            0.49473929             0.6769600
+#>  [6,]           6       0.50184228            0.41034422             0.6137425
+#>  [7,]           9       0.38269038            0.29711268             0.4929171
+#>  [8,]          12       0.29890154            0.22167479             0.4030324
+#>  [9,]          15       0.23629264            0.16877051             0.3308292
+#> [10,]          18       0.20208143            0.14274382             0.2860853
+#> [11,]          21       0.17082971            0.11580178             0.2520064
+#> [12,]          24       0.15126442            0.10079984             0.2269937
+#> [13,]          27       0.13757394            0.09019805             0.2098337
+#> [14,]          30       0.12300453            0.07677350             0.1970747
+#> [15,]          33       0.10536383            0.06049565             0.1835097
+#> [16,]          36       0.10074068            0.05720945             0.1773952
+#> [17,]          39       0.10074068            0.05720945             0.1773952
+#> [18,]          42       0.08499342            0.03811229             0.1895420
+#> [19,]          45       0.08499342            0.03811229             0.1895420
+#> [20,]          48       0.08499342            0.03811229             0.1895420
+#> 
+#> $median.random
+#>              2.5%    97.5% 
+#> 6.046385 4.826019 8.540219 
+#> 
+#> $mean.random
+#>                2.5%     97.5% 
+#> 11.929471  9.190071 14.485928
+```
+
+Plot the estimates summary survival
+
+``` r
+RandomEffectSummary<- results$summary.random
+
+plot(Time, Survival, type="n", col="grey", ylim=c(0,1),xlab="Time",
+ ylab="Survival")
+
+for (i in unique(sort(Study))){
+lines(Time[Study==i], Survival[Study==i], type="l", col="grey")
+points(max(Time[Study==i]),
+ Survival[Study==i & Time==max(Time[Study==i])], pch=15)
+}
+
+lines(RandomEffectSummary[,1], RandomEffectSummary[,2], type="l",
+ col="red", lwd=3)
+points(RandomEffectSummary[,1], RandomEffectSummary[,3], type="l",
+ col="red", lty=3, lwd=3)
+points(RandomEffectSummary[,1], RandomEffectSummary[,4], type="l",
+ col="red", lty=3, lwd=3)
+```
+
+<img src="man/figures/README-unnamed-chunk-6-1.png" width="100%" />